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Classical, Reactive, and Hybrid Agents for a Symbolic Domain.

Classical, Reactive, and Hybrid Agents for a Symbolic Domain. Lorina Na ç i Ramyaa. Overview. Introduction Agent Theory Background V-World The Built-In Agent Classical Planner Reactive Planner Hybrid Planner Conclusion. Introduction.

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Classical, Reactive, and Hybrid Agents for a Symbolic Domain.

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

  2. Overview • Introduction • Agent Theory Background • V-World • The Built-In Agent • Classical Planner • Reactive Planner • Hybrid Planner • Conclusion

  3. Introduction • Artificial Intelligenceis the computer modeling of intelligent behaviour, including but not limited to modeling the human mind. What constitutes intelligence or intelligent behaviour? • Artificial Agentsare 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. • Planning is an activity that is usually considered to need intelligence– like playing, organizing • V-World Gameisa symbolic domain which we chose for our experiments.

  4. GOFAI • 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.

  5. 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

  6. Post-GOFAI • 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.

  7. Reactive Agent Architecture Motivation: Failure of classical agent in non-ideal worlds Characteristicsof 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

  8. Hybrid Strategy • Agents need to accomplish pre-determined goals. example • Hybrid agents merge goal-orientedness and situation-orientedness. • Hybrid agents are closer to human beings.

  9. 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).

  10. 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…

  11. A V-World Agent • 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.

  12. Classical Planning Agent • It uses symbolic representation. • It is goal-oriented. • Uses the POP algorithm to plan • Example

  13. Reactive Agent • It does not use symbolic representation. • Spreading Activation • Situatedness

  14. Hybrid Agent • It uses symbolic representation. • Exploration, Survival, Planning Modes • It is goal-oriented and situation-oriented.

  15. Conclusion • 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.

  16. Thank you ?

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