Transcript UbiCom Book Figures - School of Electronic Engineering and

UbiCom Book Slides
Chapter 9: Intelligent Interaction
(All Parts, Short Version)
Stefan Poslad
http://www.eecs.qmul.ac.uk/people/stefan/ubicom
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Chapter 9: Overview
Chapter 9 focuses on:
• Internal system properties: intelligence
• External interaction with any of three types of environment
– Focussing more on ICT and physical environment
– These environments may be active, i.e., they are themselves one or
more intelligence systems
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Five main properties for UbiCom
Handling Non-determinism
Knowledge & task sharing
Goal-based, etc.
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Related Chapter Links
• There are two AI chapters that are interlinked
• Chapter 8, describes the design of single Intelligent System
or IS
– These may be simple: use a single models of intelligence
– These may be hybrid: use multiple heterogeneous intelligence
models
• This Chapter 9, describes intelligent interaction between
multiple systems
– The systems interacting may be intelligent (Chapter 8)
– The systems interacting may not necessarily be intelligent but their
interaction may still be: emergent intelligence (Chapter 10)
– Or Both
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Related Chapter Links
• Other Models of Interaction Multiplicity:
– Service Interaction (Chapter 3)
– Network Interaction (Chapter 11)
• Each type of smart device to smart environment (device)
interaction can be enhanced by making them intelligent
– CCI (Chapters 3 & 4)
– CPI (Chapters 6 & 7)
– HCI (chapter 5)
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Chapter 9: Overview
The slides for this chapter are also expanded and split into
several parts
• Part A: Interaction Multiplicity: Between peers 
• Part B: Interaction Multiplicity: Using Mediators
• Part C: Cooperative Interaction
• Part D: Competitive Interaction
• Part E: Intelligent Interaction Protocols 1
• Part F: Intelligent Interaction Protocols 2
• Part G: Multi-Agent Systems
• Part H: Social Interaction
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Part A Overview
• Basic Smart versus Intelligent Interaction? 
• Interaction Multiplicity
• P2P Interaction between Multiple Senders and
Receivers
• Unknown Sender and Malicious Senders
• Unknown Receivers
• Too Many Messages
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Introduction
• Deployment of UbiCom is  ?
• UbiCom device interaction ?
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Basic (Smart) Interaction
• P2P Interaction
• Interaction that involves passive intermediaries
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Intelligent (Smart) interaction
What is Intelligent (Smart) interaction?
• Beyond using universal network communication protocols,
• Involves Coordination
• Use of Semantics
• Communicate using a rich language
• Organisational interaction
• etc
Intelligent interaction is built upon basic interaction
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Intelligent Interaction
2 dimensions of intelligent interaction
• Interaction between multiple intelligent systems & their
environments
• Intelligent Interaction between relatively non-intelligent
multiple systems & environments
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Smart Device versus Intelligent Device
Interaction
Interaction between smart devices (Chapter 1):
• Digital,
• Connected,
• Degree of local autonomous control, etc
Interaction between intelligent devices (Chapter 8):
• Specific notions of intelligence,
– e.g., reflexive, goal-based etc
• Different degrees of intelligence (Chapter 13)
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Intelligent Environment versus
Intelligent Interaction
Intelligent Environment:
• Environment for a system, is intelligent
• Environment may include other intelligent systems
Intelligent Interaction:
• Interaction, between a system and its environment
(including other systems), is intelligent
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Interaction Multiplicity
• Interaction multiplicity can occur in many different
components of UbiCom systems & their environments, e.g.,
– ICT Environment (C)
• Services (S)
• Networks (N).
– Human Environment (H)
– Physical Environment (P)
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Basic Interaction Multiplicity
Example: Service Invocation
Types of Interaction Multiplicity
Interaction Multiplicity
• Interaction multiplicity  complexity of interaction. Why?
• How to manage  complexity of Interaction multiplicity?
– .
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Interaction Multiplicity Examples:
Communication
Chapter 9: Overview
The slides for this chapter are also expanded and split into
several parts
• Part A: Interaction Multiplicity: Between peers
• Part B: Interaction Multiplicity: Using Mediators 
• Part C: Cooperative Interaction
• Part D: Competitive Interaction
• Part E: Intelligent Interaction Protocols 1
• Part F: Intelligent Interaction Protocols 2
• Part G: Multi-Agent Systems
• Part H: Social Interaction
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Part B Overview
•
•
•
•
Interaction using Mediators
Shared Communication Resource Access
Shared Computation Resource Access
Mediating Between Requesters and Providers
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Mediated Interaction
• Mediator: a go between interacting participants / peers
– also referred to as 3rd parties, intermediaries, middle- ware -agents
• Benefits:
– Enhances peer discovery and service discovery
– Etc
• Disadvantages:
– Performance drops as extra intermediate nodes / hops are used
– etc
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Mediated Interaction
• The following types of mediated interaction:
–
–
–
–
Shared Communication Channel Access
Shared Computation Resource Access
Service Discovery
etc
• Can be considered in terms of:
– Motivation?
– Challenges?
– Handled by?
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Mediating Between Requesters and
Providers
• Mediators enhance peer discovery & service discovery
• Instead of having to request information from each peer,
info. accessed in 1 place, a 3rd party at a well known,
static, address uses well standardised directory interface
• 2 types of information used in discovery process
– service capability
– Service preferences
• Different designs for mediators exist depending on how
service capabilities or preferences are kept private versus
shared
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Who Knows Requests & Preferences
Mediators
Who Knows Capabilities
Mediator Design Issues
• When are Mediators used during an interaction?
• Support for anonymity
• Mediators can be designed to support a range of different
representations for capabilities and preferences
• Mediators can be designed to support different types of
interaction
• Mediator fairness to providers
• Trust & Neutrality
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Mediators: Interaction Protocols
• What interaction protocols should these different types of
mediator use?
– Request-reply?
– Asynchronous notifications?
– Other protocols?
But how can we support richer & more flexible interaction?
See later
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Chapter 9: Overview
The slides for this chapter are also expanded and split into
several parts
• Part A: Interaction Multiplicity: Between peers
• Part B: Interaction Multiplicity: Using Mediators
• Part C: Cooperative Interaction 
• Part D: Competitive Interaction
• Part E: Intelligent Interaction Protocols 1
• Part F: Intelligent Interaction Protocols 2
• Part G: Multi-Agent Systems
• Part H: Social Interaction
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Part C Overview
•
•
•
•
•
•
•
Interaction using Cooperative Participants 
Coordination Basics
Perfectly Coordinated Systems
Coordination design issues
Coordination through join intentions and plans
Coordination using Norms and Electronic Institutions
Hierarchical and Role-based Organisational Interaction
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Interaction Multiplicity: Cooperative
Interaction
• Cooperative interaction enables multiple systems to work
together.
Characterised by 2 main properties:
• Coordination: synchronising activities
• Cohesion: acting together (organisational interaction).
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Interaction Multiplicity: Cooperative
Interaction
• Cooperation is easier to manage when:
–
–
–
–
–
homogeneous designed systems interact;
there is centralised control;
systems are designed as pure servers
systems are designed statically to cooperate;
systems act benevolently and reliably.
• Cooperation is harder to manage when:
–
–
–
–
–
–
different systems are designed by independent developers;
systems are designed to act autonomously;
systems support heterogeneous goals;
systems need to cooperate dynamically;
parties may act in a self-interested manner;
systems act malevolently and may non-deterministically
malfunction.
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Cooperative Interaction: Pros and
Cons
Advantages of Cooperative Model
Disadvantages of cooperative model
Distributed problem solving: solves it Cooperation
reduces
and
quicker as more parts are processed in competition can 
parallel.
Delegation: Don’t need to do everything Communication, costs, unreliability
ourselves. Don’t want to do it ourselves, may outweigh the extra processing
too time-consuming. Instead delegate
benefits of the distribution.
Selection: select best option from a set of Coordination & management is
candidates
more complex: disruptions (insider
attack), lack of understanding,
ambiguity, conflict.
Reliability: there are alternative options. Delegation and session initiation
costs too high
Social: agents act on behalf, to engage Lack of control, privacy.
people
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Cooperative Interaction: coordination
• Explicit Coordinated Cooperation
• Coordination using Norms and Electronic Institutions
• Hierarchical and Role-based Organisational Interaction
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Coordination: Classification
Message-based vs. process-based
Explicit vs. Implicit
Perfect vs. imperfect
etc
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Coordination Design Issues
• Whether or not ISs are spatially and or temporally
coincident, or not
• Handling inconsistencies and uncertainty. How?
–
• Who Coordinates?
–
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Coordination Classification
Explicit coordination
• Service composition(Section 3.3.4).
• Interaction protocols with inbuilt coordination mechanisms
– See later
• Joint planning
• Joint intentions
Implicit coordination
• Norms and Electronic Institutions
• Hierarchical & Role-based Organisational Interaction
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UbiCom System Applications of
Social Organisations
Provide a flexible way to design a large range of
organisations
• to dynamically configure building facilities to support
building energy efficiency;
• for personalised work environments
• for information integration and interoperability
• information services for mobile users in which IS
dynamically adapt information to multiple contexts such as
location, person and ICT system.
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Chapter 9: Overview
The slides for this chapter are also expanded and split into
several parts
• Part A: Interaction Multiplicity: Between peers
• Part B: Interaction Multiplicity: Using Mediators
• Part C: Cooperative Interaction
• Part D: Competitive Interaction 
• Part E: Intelligent Interaction Protocols 1
• Part F: Intelligent Interaction Protocols 2
• Part G: Multi-Agent Systems
• Part H: Social Interaction
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Part D Overview
•
•
•
•
Interaction with Self-interested Participants 
Market-based Interaction and Auctions
Negotiation and Agreements
Consensus-based Agreements
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Competitive Interaction
•
Cooperation vs. Competition
– cooperators share their goals with collaborating parties & act
together
– competitors keep their goals private & act self-interestedly.to further
their own goals, rather on collaborating to help further others’ goals
• As diverse smart autonomous, configurable, networked
devices  in physical spaces, competitive interaction 
• Design models to solve the associated resource conflicts
and resource allocation problems will become essential.
• E.g., in Smart utility regulation scenario.
– Multiple autonomous lighting devices in smart environment, all seek
to switch themselves on but some are redundant & wastes energy.
– Multiple users may seek to configure a shared or multiple devices
that overlap in function in multiple ways, e.g., multiple users wish to
regulate heating and lighting levels differently.
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Competitive Interaction
• Different types of competitive interaction problems and
designs depending on:
–
–
–
–
No. of players
interaction protocols;
Strategies;
Nature of the completion
• Self-interested interaction is complicated further when
participants act maliciously, i.e., lie and collude.
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Interaction Multiplicity: Competitive
Interaction Types
• Market-based Interaction and Auctions: used to allocate
resources to individual requesters
• Negotiation and Agreements: more general than auctions,
used in market places to agree terms but can also be more
generally used to resolve conflicts.
• Convergence: a multi-step processes where two or more
entities iteratively reach an agreement. Convergence
algorithms and protocols tend to be domain specific
• Consensus based protocols can be used to reach
agreement between multiple participants, but normally for
one object at one time, e.g., voting protocols
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Competitive Interaction: Designs
• A generic problem for UbiCom is allocation of limited
resources & services to multiple self-interested requestors.
Designs to manage this?
• Control can be more generally acceded to a third party
• Concurrency control (Section 9.2.2.2).
• Policy based management (Section 12.2.8.4)
• Market-based Interaction and Auctions
• Negotiation and Agreements
• Consensus-based Agreements
• Can we classify these designs into types of mediator
(passive versus active) & mediated versus non-mediated?
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Auctions
• Is 1 of oldest but still widely-used market based protocols
• Designed to allocate resources such as goods and services
to one of the bidders.
• Several types of auction protocol depending on
– ????
• Auction Benefits
– ???
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Auctions
• Different types of auction?
• English auction, can be classified in terms of the following
properties for bids:
–
–
–
–
a single type of goods
single attribute
single sided
ascending
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Negotiation & Agreements
• Auctions are designed to reach agreements between
sellers and consumers in a market-place
– are considered to be a type of more general technique called
negotiation.
• General aims of Negotiation is modification of local agent
policies to constrain interaction and plans of interaction,
– e.g., in the case of negative (harmful) interactions, and identification
of situations where new potential interactions are possible and
beneficial.
• Uses of negotiation in UbiCom?
–
–
–
–
task and resource allocation;
recognition of conflicts;
resolution of goal disparities;
determination of the organisational structure and hence for
organisational
coherence.
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Negotiation Design
In general a negotiation method has 4 principle components:
• Public shared interaction protocol
• Deal rule
• Negotiation set
• Strategies that are kept private
Design properties for negotiation protocols ?
• pareto optimal,
• stable
• individually rational
• support computation and communication efficiency
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Negotiation Designs
• Negotiation can be considered to be a distributed search
– Search is through a space of potential agreements (chapter 8)
• Game-theory is used to develop strategies between
competing players who strive to win a game
• Argumentation-based negotiation allows additional
information to be exchanged, over and above proposals
• Different problem domain models for negotiation
applications:
– Task-based
– State-based
– Worth-based.
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Consensus-based Agreements
• Consensus based interaction can be used to reach an agreement when
multiple self-interested participants share a common goal
• Consensus is important when different participants or processes
interact such that their self-interested goals may conflict
• Consensus refers both to a state of agreement that is reached by
independent participants and to the process to reach an agreement.
• Consensus may also be useful in situations where there are several
alternatives but it is not clear which one alternative should be chosen,
• In contrast to negotiation, consensus based agreements are simpler.
How?
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Chapter 9: Overview
The slides for this chapter are also expanded and split into
several parts
• Part A: Interaction Multiplicity: Between peers
• Part B: Interaction Multiplicity: Using Mediators
• Part C: Cooperative Interaction
• Part D: Competitive Interaction
• Part E: Intelligent Interaction Protocols 1 
• Part F: Intelligent Interaction Protocols 2
• Part G: Multi-Agent Systems
• Part H: Social Interaction
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Part E Overview
• IS Interaction Design 
• Designing System Interaction to be more Intelligent
• Designing Interaction between Individual Intelligent
Systems
• Interaction Protocol Design
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IS Interaction Design
2 basic dimensions to supporting intelligent interaction:
• to design conventional system interaction to be intelligent
• to design individual intelligent systems to interact
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More Intelligent Conventional system
Interaction
Motivation
• Mediation & handling heterogeneity
• Reflection about communication
• Distributed problem solving
• Task delegation
• Flexibility and Selection
• Reliability
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Interaction Between Individual ISs:
Motivation
• Part of the motivation for individual intelligent systems to
interact with each other, is to handle the knowledge
bootstrapping problem. How?
• Single intelligent entity needs to independently learn
everything it needs to know itself
• Single intelligent entity would also need its own internal,
complete, knowledge model of the world and of itself,
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IS Interaction: Design Issues
Interaction design issues:
• If common, extensible message protocol can be designed
for use across multiple types of UbiCom interaction
•
• If ISs need to share and fix a common understanding of
terms or concepts within a domain
•
If ISs need to share the some context associated with a
message,
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IS Communication Protocols
• Involves specifying 2 separate (sub-) application layer
protocols:
– specifying individual messages (Message Protocols)
– Specifying patterns of multiple messages (Interaction Protocols)
• Message protocols define
– ????
• Interaction protocols define
– ????
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Interaction Protocol Types
• Individual messages are not used in isolation but used in
different patterns of multiple messages
Classification of Interaction Protocols?
• Information sharing vs. task sharing
• Unicast versus Multicast
• Pull versus Push
• Syntactic versus Semantic versus Linguistic
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Handling Interaction Failures
How can the following interaction failures be handled?
• Network link failure
• Receiver down, not ready
• Wrong message syntax
• Use wrong default values, types
• Use of service constraints that cannot be satisfied by
provider
• Unknown service providers and location
• Client action, e.g., sender cancel
• Messages as part of processes not coordinated
• Semantic differences in use of terms at sender & receiver
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Interaction Protocol Design Issues
• Interaction protocols are often designed to be servicespecific and domain specific
– -> service interoperability is challenging
• Interaction protocols are fixed, not very extensible
– Although multiple interaction protocols can be orchestrated
• Can introduce interaction flexibility
– through use of cooperative dialogues
– Explicitly supporting, nesting, concurrency etc
• Can add interaction richness
– Through use of semantic protocols to define meaning, context of
interaction
– But how to define the semantics
– Using, OWL, Speech Acts?
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Chapter 9: Overview
The slides for this chapter are also expanded and split into
several parts
• Part A: Interaction Multiplicity: Between peers
• Part B: Interaction Multiplicity: Using Mediators
• Part C: Cooperative Interaction
• Part D: Competitive Interaction
• Part E: Intelligent Interaction Protocols 1
• Part F: Intelligent Interaction Protocols 2 
• Part G: Multi-Agent Systems
• Part H: Social Interaction
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Part F Overview
• Semantic and Knowledge Sharing Protocols 
• ACLs and Linguistic-based Protocols
• Examples of use of Interaction Protocols in PM Scenario
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Semantics of Communication
Protocols
• Communication protocols (CP) are specified in terms of
human-readable but not in machine-readable semantics.
• Lack of a standard semantic representation for protocols
Can standard KRs for content, e.g., OWL, be used for CP?
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IS Message Protocols Based Upon
Speech Acts
• Based upon type of linguistic protocol called Speech Acts
• Some speech utterances are like physical actions that
change the state of the world,
– e.g., pronouncing someone as ‘man & wife’ in a religious ceremony,
– sending message to set a new fact that changes the state of KB.
• Basic structure of speech act defines:
– Type of action
– Pre-conditions which if true enable actions to be triggered.
– Post-conditions of effects define what should now be true if the action
was successfully executed.
• The most useful types of communicative acts are
– Assertives: set (information, facts, system states)
– Directives: task requests, info. queries, mediating actions
– Phatics: establish, check, prolong and interrupt, control comms
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Speech Act Model Benefits
• Why used be speech act-based interaction between ISs?
– Rather than conventional communication protocols between Iss
• Generic model of communicative acts could be used
across all knowledge domains, enhancing service
interoperability.
• In contrast, currently, each application domain and even
multiple applications within that domain specify their own
sets of service actions.
– This makes interoperability using service actions defined in
heterogeneous service models complex.
• Some instantiation of service actions is needed to ground
the semantics
– this could vary across services and service domains.
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Speech Act
Semantic specifications for ACLs:
• BDI
• Contract programming model semantics
• Semantic Commitments based upon social conventions
• IP context can be used as the semantics for the
communicative act.
– E.g., FIPA Interaction Protocol model makes a rudimentary attempt
at a social model in the sense that the interaction is related to the
organisational roles of the interacting parties and the semantics of
each CA in an IP is interpreted within the context of the IP.
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Interaction Protocol Example:
Request
• Specifications of communication using speech acts
– how multiple communicative acts can be used as part of different
interaction patterns
– how a communicative act links to the message content
• Request interaction pattern
– Classification: a task-sharing one-to-one pull type interaction
• Although it seems similar to a client-server type requestresponse pattern, it is more flexible in several ways
– responder can optionally choose to acknowledge request & supply
the result later.
– responder also has different options to signal:
• lack of understanding of the request,
• failure for some reason such as lack of sufficient ICT resources
• refusal where although it could do the task for some reason, it chooses
not to.
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Interaction Protocol Example:
Request
ELEM007 Agents
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Interaction Protocol Use in PM
Scenario
• As an example of the benefits of using rich and flexible
interaction protocols, resource access is considered during
personal memories (PM) scenario
– e.g., accessing and displaying or playing audio-video content.
• In the simple case, we invoke an AV-player (service)
passing the details of the source of the AV content of our
choice.
• But when we play the AV source it fails, the system must
then decide how to proceed?
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Interaction Protocol Use in PM
Scenario
• Typically, requester asks for assistance by searching for
help in a well-known place a directory.
• Once the requester finds a help assistance, the requester
can choose to delegate the resource access task to the
help assistant
– providing some conditions were fulfilled such as authentication and
competency checks were fulfilled
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Interaction Protocol Use in PM
Scenario
In more detail,
• A Help peer registers itself with provider to be informed
when its fail to fulfil a request from a requester (a
subscribe).
• The Help peer then announces itself to the requester. The
requester then queries Help about use of a resource X.
• Help advices A to ask resource depository D something.
• D tells the requester that peers E,F,G, H have resource X.
• Requester issues a contract (a call for proposals or cfp) to
E,F,G,H to ask them to bid to supply the resource as A does
not know which of these can provide the resource most
favourably
• etc.
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Interaction Protocol Use in PM
Scenario
Resource
Requester
Resource
Repository
Help Assistant
request
query
inform
inform
query
inform
inform
Delegating task of resource access to a help assistant
Chapter 9: Overview
The slides for this chapter are also expanded and split into
several parts
• Part A: Interaction Multiplicity: Between peers
• Part B: Interaction Multiplicity: Using Mediators
• Part C: Cooperative Interaction
• Part D: Competitive Interaction
• Part E: Intelligent Interaction Protocols 1
• Part F: Intelligent Interaction Protocols 2
• Part G: Multi-Agent Systems 
• Part H: Social Interaction
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Part G Overview
•
•
•
•
Multi-Agent Systems 
ACL and Agent Platform Design
Multi-Agent System Application Design
Some Generic Intelligent Interaction Applications
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Multi-Agent Systems (MAS)
• Generally, if an IS is represented by an agent, then a MAS
represents multiple interacting IS.
• When MAS interact with other MAS they represent systems
of systems interacting.
• Can characterise the properties of MAS?
–
–
–
–
–
•
degree of dynamism
degree of scale (numbers of agents)
type of (organisational) control
homogeneous versus heterogeneous types of individual agent
type of agent interaction (e.g., goal exchange, belief exchange etc).
Use of an appropriate ACL (Agent Communication
Language) can support these MAS properties.
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Agent Platform or Middleware Design
• Common Multi-Agent Systems (MAS) consists of:
– Agent Interaction Protocol Suite (AIPS): individual agents interact
using an Agent Communication Language
– Agent Platform or Middleware accessed through some API
– MAS Applications
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Agent Platform or Middleware Design
• Core agent middleware services typically include:
– ACL interaction
– agent name / agent life-cycle management
– directory facilitator service
• Should each service be an agent?
• Several agent toolkits have been developed which support
the FIPA ACL and agent platforms , e.g., JADE
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Agent Interaction Protocol Suite
• In terms of the TCP/IP protocol suite,
• ACL behaves as a suite of multi-layer protocols at the
application level
– for this reason has been termed an AIPS or Agent Interaction
Protocol Suite or AIPS
• Several protocols are needed to support interaction for
intelligent applications using communicative acts:
–
–
–
–
an interaction protocol
a communicative act protocols
a content protocol.
Content protocol may separate the content Ontology from a content
logic. Why?
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Agent Interaction Protocol Suite
MAS Application Design
• Many examples of IS or Agent-Oriented Software
Engineering (AOSE) methodologies (also called AgentOriented Development or AOD).
• There are 2 basic types:
– those which extend or adapting non-Is system methodologies, e.g.,
object-oriented based AOSE
– those based upon AI methodologies.
– Hybrid methods
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MAS Application Design
• AOSE design can be captured in two main model views:
– organisational view: specifies types of agents & roles
– operational view: specifies interaction constrained by goals and
plans of actions to achieve those goals.
• (Organisational) Roles support a more dynamic approach.
• Roles used to separate responsibility for service access
from identity to:
– enable agents to combine multiple roles;
– enable several agents to play same role (redundancy);
– enable agents to change roles at run time;
• Plans: order system (internal) actions & (external)
interactions
– interactions that determine the roles of entities in the organisation
•
.
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Organisational Model for Part of PM
Scenario
Operational Model for Part of PM Scenario
Operational Model for Part of PM
Scenario
• Example of an operational view is a simple task-oriented
description of a problem
• Goal is to display images from the digital camera peer on
some (visual) display, i.e., part of the personal memories
scenario.
• Goal is normally achieved using a very simple default plan
which in this case consists of a sequence of two actions:
– AV source peer such as a digital camera or its storage media
requests use of image reading functions of an AV player which is
connected to a display
– Provider then responds by signalling to the AV source that the
display is ready.
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Chapter 9: Overview
The slides for this chapter are also expanded and split into
several parts
• Part A: Interaction Multiplicity: Between peers
• Part B: Interaction Multiplicity: Using Mediators
• Part C: Cooperative Interaction
• Part D: Competitive Interaction
• Part E: Intelligent Interaction Protocols 1
• Part F: Intelligent Interaction Protocols 2
• Part G: Multi-Agent Systems
• Part H: Social Interaction 
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Part H Overview
• Social Networking & Media Exchange 
• Recommender Systems
– Content-Based
– Collaborative Filtering
• Referral Systems
• Pervasive Work Flow Management for People
• Trust Management
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Introduction
• There are many intelligent interaction applications which
can be classified into:
– CCI, e.g., autonomous systems;
– HCI
– CPI.
• This section focuses on social type HCI type interaction
models and their application to CCI and CPI.
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Social Networking and Media
Exchange
• Humans have an instinctive need to communicate, to
socialise
• Providing content for public and private access is now
cheap relative to the average standard of living.
•  Remote Social interaction
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Social Networking and Media
Exchange: Challenges
•  Remote Social interaction but at the expense of  Local
social interaction
• Inclusion: requires ICT resources not affordable for
everyone, everywhere?
• New means of delivering content leaves us open to the
potential hazards that exist in the physical world?
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Social Networking and Media
Exchange: Semantics
• Semantics used to enable semantic interoperability,.
•
This misuse can potentially benefit from the semantics.
Why?
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Social Media
• Social Media experience can take many different forms,
including text, images, audio, and video.
• Popular mediums include:
–
–
–
–
–
Blogs & Microbloggs, e.g., twitter
Social networks,
Content communities (sometimes called folksonomies)
podcasts
wikis,
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Social Media: Organisation
• In general the trend is that large amounts of content is
created and shared by users and a stronger move to Web
as a user-driven application platform.
• It is not feasible to expect even the diligent users to
annotate and add details to their content and organise this
in a methodical and consistent.
• To help the users to manage and organize their content
requires certain contextual knowledge that comes from a
number of places
– e.g. content annotations, semantic metadata, contact lists, the way
the user organises contact lists as family and friends, etc.
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Social Media: Organisation
• To organize content for users requires that a system has
certain pertinent and significant knowledge about users,
their context & habits.
• Creation of contextual knowledge & use of contextual
knowledge can help user to manage & share their content
• Challenge in any solution is in the way the knowledge is
aggregated to provide a contextual filter that can be applied
to the organization of the content.
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Social Media: Organisation
There are different techniques to filter and organise media
• Personalisation
• Self-organisation
• Self-governance
.
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Recommender Systems
• Recommenders are types of personalisation software
• Is often viewed as crucial for e-commerce sites.
• There are two main types of recommender system:
– Content-based filtering
– Collaborative-filtering
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Recommender Systems
• Examples of the use of recommender system for Ubicom?
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Referrals
• Referrals are trusted recommendations by known people,
in contrast to recommendations that are anonymous.
• For serious life and business decisions, people often value
the opinion of a trusted expert more, rather than an
anonymous decision.
• Discuss how referral (chains) work here
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Pervasive Work Flow Management for
People
• Physical distance is much less of a barrier for
communication and workflow
• Virtual distance between employees in terms of differing
beliefs, systems and experiences is still a barrier.
•  Effectiveness of the cooperation between them. Why?
– Lack of trust between different layers of organisation
• Solutions?
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Trust
• Trust is an inherent property in UbiCom systems in which:
– one autonomous component cannot completely control another
autonomous component
– but which may need to rely or one another or require some
cooperation from it.
• Trust in social organisations, is a general expectation,
explicitly, evaluated, that one autonomous component, the
truster, can rely on another autonomous component, the
trustee, in order to share information, tasks, goals, etc, with
them.
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Trust Design Issues
• There are several dimensions or metrics to specify trust for
use in open UbiCom systems?
– personal trust or impersonal trust
– the disposition of the truster to trust, which ranges from being
averse to trust to being eager to trust
– if distrust is modelled as the complete absence of trust (zero trust)
or is considered in terms of negative metrics for trust
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Trust-based Management
• Social control based upon trust is sometimes referred to as
a soft security in contrast to hard security which is control
based on encryption type algorithms.
• Soft security is viewed as a more effective mechanism for
security, in terms of robustness, scalability, and adaptability,
in pervasive environments such as information-sharing
communities that support inter-organisational interactions
• The relationship or dependency of the truster on the trustee
is referred as a trust relation.
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Social Trust Use in UbiCom
• In many computer systems, although a notion of trust may
be implied, such as the use of a trusted platform, or a
trusted third party, there is often no explicit computation
model of trust incorporated.
• Trust is more useful issue for external interaction rather
than internal interaction.
• Internal interaction is often designed to use well-defined
notions of control which can obviate the need for trust.
• In external interaction between one autonomous system
and its environment or another autonomous system, use of
a centralised control mechanism is not possible by design.
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Social Trust Use in UbiCom
• Sometimes there are concepts which are akin to trust used
in distributed systems?
– System may define a QoS for another peer to provide
– Requester can examine the collective reputation of another peer
before deciding to interact with it.
• Peers are also often defined to be eager to trust, to blindly
trust, This is referred to as an ad hoc trust model.
– e.g., if the provider has a service description in well-known directory
then the provider must be trustworthy, etc.
• Of course the directory may offer no control or checks
about whether or not malicious providers can offer services
or malicious clients can search for services,
– hence blind trust in the directory service can be associated with an
unknown trust relation between one peer and another.
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Social Trust Models Use in UbiCom
• Benefits?
•
Ways to incorporated trust in a computation form in
UbiCom systems.
– Authentication-based policy systems based upon PKI.
– Authorisation-based policy systems such as SPKI,
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Social Trust Model Use in Intelligent
Systems
• Many applications of multi-agent-system models use
collaborative type filtering mechanisms
– E.g., based upon recommendations and reputations as well as
policy-based MAS models to support impersonal trust.
•
2 main aspects of design trust for Multiple IS.
– to allow agents to trust each other -> need to endow them with the
ability to reason about reciprocative nature, reliability, or honesty of
their counterparts.
– to design protocols and mechanisms of interactions such that
participants will find no better option than telling the truth and
interacting honestly with each other.
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Summary & Revision
For each chapter
• See book web-site for chapter summaries, references,
resources etc.
• Identify new terms & concepts
• Apply new terms and concepts: define, use in old and
new situations & problems
• Debate problems, challenges and solutions
• See Chapter exercises on web-site
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Exercises: Define New Concepts
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Exercise: Applying New Concepts
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