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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