Transcript Classical, Reactive, and Hybrid Agents for a Symbolic Domain. Lorina Naçi

Classical, Reactive, and
Hybrid Agents for a Symbolic
Domain.
Lorina Naçi
Ramyaa
Overview
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Introduction
Agent Theory Background
V-World
The Built-In Agent
Classical Planner
Reactive Planner
Hybrid Planner
Conclusion
Introduction
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Artificial Intelligence is the computer modeling of intelligent
behaviour, including but not limited to modeling the human mind.
What constitutes intelligence or intelligent behaviour?
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Artificial Agents are systems which perceive and act. They are
systems that instantiate chosen model of intelligence. Different
definitions or notions of intelligence give rise to different models – and
so, different agent architectures.
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Planning is an activity that is usually considered to need
intelligence– like playing, organizing
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V-World Game is a symbolic domain which we chose for our
experiments.
GOFAI
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AI should emulate human intelligence.
The world is made of symbols.
Rationality involves symbol crunching.
Intelligence is delineated by rationality
Rationality is largely the pursuit of goals.
Hence, classical planning agents are symbolic and
goal oriented.
Classical Agent Architecture
Motivation: Traditional model of intelligence
Characteristics of Classical Planning:
It uses symbolic representation of world states.
It has an initial state, operators, pre and post conditions,
and a goal state.
Assumptions:
The world is deterministic, accessible, static,symbolic,and
its operators can be fully specified.
Strengths: Sound, Complete, Predictable
Weaknesses: Brittle
Post-GOFAI
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AI should emulate intelligent behavior.
The world is complex and non-symbolic.
Complex behavior arises due to the complexity of
the environment.
• Agents must be situation-oriented.
• Reactive agents are situation-oriented, but can be
too reactive.
Reactive Agent Architecture
Motivation: Failure of classical agent in non-ideal worlds
Characteristics of Reactive Planning:
It uses no central control and no representation; it is
situation-oriented and data driven.
Assumption:
The world is unreliable.
Strengths: More robust than classical planning. Fast.
Weaknesses: Unpredictable
Hybrid Strategy
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Agents need to accomplish pre-determined goals.
example
• Hybrid agents merge goal-orientedness and
situation-orientedness.
• Hybrid agents are closer to human beings.
Hybrid Agent Architecture
Motivation: Inability of reactive to do achieve goals.
Characteristics of Hybrid Planning:
It is goal-oriented and situation-oriented.
Assumption:
The world is unreliable, but the agent must fulfill certain
goals.
Strengths: Robust; More predictable than reactive strategies.
Weaknesses: Needs to account for all possible situations
(needs too much specification).
V-World
What is V-World?
• A symbolic test bed for artificial agents.
• It contains objects and interacting creatures.
• It is non-deterministic, static, discrete, non-accessible,
tractable, etc.
• It accommodates the different planning architectures.
Castle World
• Has a specific ontology.
• The goal of the game is…
A V-World Agent
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It has two utility functions: strength and damage.
It has a pre-defined interaction with the objects and the
creatures in the world.
It can see a 5 X 5 square centered on itself.
It can move one step in any of the 8 directions or choose to
sit.
Classical Planning Agent
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It uses symbolic representation.
 It is goal-oriented.
 Uses the POP algorithm to plan
 Example
Reactive Agent
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It does not use symbolic representation.
 Spreading Activation
 Situatedness
Hybrid Agent
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It uses symbolic representation.
 Exploration, Survival, Planning Modes
 It is goal-oriented and situation-oriented.
Conclusion
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Classical planning agents: “specific-tools.”
Reactive and hybrid agents: “general-purpose
tools.”
V-World is a flexible test-bed.
Reactive and hybrid agents are better suited for a
wider range of domains.
Reactive and hybrid agents are more similar to
human beings.
Thank you
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