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Advanced AI

Explore the different goals, functions, and properties of automated agents in artificial intelligence, covering topics such as interaction with environments, adaptability, autonomy, and learning capabilities. Learn from expert lectures by Prof. Sarit Kraus and adjust slides from Harvard Univ.

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Advanced AI

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  1. Advanced AI Prof. Sarit Kraus Bar-Ilan University Slides adjusted from David Parkes from Harvard Univ. 89-950 Lecture 1

  2. Different Goals of AI 89-950 Lecture 1

  3. sensors percepts ? environment agent actions actuators An agent and its environment agent :Something that takes input (percepts) from its environment through sensors and takes actions upon its environment, using actuators. agent function: mapping from percept sequence to an action 89-950 Lecture 1

  4. Automated Agents • Autonomous • Plan • Adaptive • Able to learn • Cooperate with other agents or people • Can face adversary

  5. What is an Agent? PROPERTY MEANING • Situated Sense and act in dynamic/uncertain environments • Flexible Reactive (responds to changes in the environment) • Autonomous Exercises control over its own actions • Goal-oriented Purposeful • Persistent Continuously running process • Social Interacts with other agents/people • Learning Adaptive • Mobile Able to transport itself 89-950 Lecture 1

  6. Properties of environments Observable vs. Partially-observable (complete state of world is available to agent) Deterministic vs. no-deterministic (Stochastic) (no uncertainty about effects of actions) Static vs. Dynamic (do not need to observe while deliberate) Discrete vs. Continuous (state/percepts/actions/time) Single vs. Multiagent (cooperative vs. competitive) 89-950 Lecture 1

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