Agents are autonomous that is they act on behalf of

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How is an Agent different from other software? Agents are  autonomous , that is they act on behalf of the user  Agents contain some level of  intelligence , from fixed rules to  learning engines that allow them to adapt to changes in the  environment Agents don't only act  reactively , but sometimes also  proactively   Agents have  social ability , that is they communicate with the user,  the system, and other agents as required  Agents may also  cooperate  with other agents to carry out more  complex tasks than they themselves can handle  Agents may  migrate  from one system to another to access remote  resources or even to meet other agents 
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29 Environment Types Characteristics Accessible vs. inaccessible Deterministic vs. nondeterministic Episodic vs. nonepisodic Hostile vs. friendly Static vs. dynamic Discrete vs. continuous 
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30 Environment types Environment Accessibl e Deterministic Episodic Static Discrete Operating  System Virtual Reality Office  Environment Mars
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31 Environment types Environment Accessibl e Deterministic Episodic Static Discrete Operating  System Yes Yes No No Yes Virtual Reality Yes Yes Yes/No No Yes/No Office  Environment No No No No No Mars No Semi No Semi No The environment types largely determine the agent design.
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32 Structure of Intelligent Agents Agent = architecture + program Agent program:  the implementation of  P    A, the agent’s  perception-action mapping function : Skeleton-Agent( Percept returns   Action memory   UpdateMemory(memory,  Percept ) Action   ChooseBestAction(memory) memory   UpdateMemory(memory,  Action ) return   Action Architecture:  a device that can execute the agent program (e.g.,  general-purpose computer, specialized device, beobot, etc.)
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33 Using a look-up-table to encode f : P* A Example:  Collision Avoidance Sensors: 3 proximity sensors Effectors: Steering Wheel, Brakes How to generate? How large? How to select action? agent obstacle sensors
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34 Using a look-up-table to encode f : P* A Example: Collision Avoidance Sensors: 3 proximity sensors  Effectors: Steering Wheel, Brakes How to generate: for each  p P l × P m × P r generate an appropriate action,  a S × B How large: size of table = #possible percepts times # possible  actions = | P l | | P m | | P r | | S | | B | E.g., P = {close, medium, far} 3 A = {left, straight, right}  ×  {on, off} then size of table = 27*3*2 = 162 How to select action? Search. agent obstacle sensors
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35 Agent types Reflex agents Reflex agents with internal states Goal-based agents Utility-based agents
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36 Reflex agents
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37 Reactive agents Reactive agents do not have internal symbolic models.  Act by stimulus-response to the current state of the environment. 
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