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NCSU CSC 411 - Exam 1 Study Guide

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CSC411 1st Edition Exam # 1 Study Guide Lectures: 1 - 7Chapter 2 – Agents and Environments- Agentso Perceive (sensors)o Act (actuators)- PEAS o Performance measureo Environmento Actuatorso Sensors- Exampleso Part-picking roboto Chess-playingo Taxi drivingo Poker-playing- Types of Environmentso Partially Observable vs. Completely Observable Ex. Chess is completely observable, taxi driver is noto Static vs. Dynamic Does the environment change as the agent is making decisions? (chess is static, taxi driving is dynamic)o Stochastic vs. Deterministic Is the outcome guaranteed?o Single vs. Multiagento Episodic vs. Sequential Do previous actions matter? (Poker is sequential)o Discrete vs. Continuous- Four Types of Agento Simple Reflex Agent (if-then) Only works in fully observable environmento Model-Based Reflex Agento Goal-Based Agento Utility-Based AgentChapter 3 – Problem Solving Through Search- Task  Grapho State spaceo Initial stateo Actionso Transition functiono Goal state- Uninformed Searcho Breadth-First Search (BFS)o Depth-First Search (DFS) Limited-depth DFSo Iterative Deepening Algorithm (IDA)o Bi-Directional Searcho Uniform Cost Search- Informed Searcho Best First Greedy: f(n) = h(n) A*: f(n) = g(n) + h(n)Chapter 4 – Optimization - State Representation- Evaluation Function- Local Operator (given)Categories of Algorithms- Hill Climbing- Simulated Annealing- Local Beam Search (k)- Genetic Algorithm (fitness


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NCSU CSC 411 - Exam 1 Study Guide

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