MIT16_410F10_lec02

MIT16_410F10_lec02 - Problem Solving as State Space Search...

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1 Brian Williams, Fall 10 1 Problem Solving as State Space Search Brian C. Williams 16.410-13 Sept 13 th , 2010 Slides adapted from: 6.034 Tomas Lozano Perez, Russell and Norvig AIMA Brian Williams, Fall 10 2 Assignments • Remember: Problem Set #1: Java warm up Out last Wednesday, Due this Wednesday, September 15 th • Reading: – Today: Solving problems through search [AIMA] Ch. 3.1-4 – Wednesday: Asymptotic Analysis Lecture 2 Notes of 6.046J; Recurrences, Lecture 12 Notes of 6.042J.
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2 Brian Williams, Fall 10 3 Recap - Course Objectives 1. Understand the major types of agents and architectures : – goal-directed vs utility-based – deliberative vs reactive – model-based vs model-free 2. Learn the modeling and algorithmic building blocks for creating agents: Model problem in an appropriate formal representation . Specify , analyze, apply and implement reasoning algorithms to solve the problem formulations. Brian Williams, Fall 10 4 Plan Execute Diagnosis Locate in World Plan Routes Map Maneuver and Track Mission Goals Recap – Agent Architectures Functions: Robust, coordinated operation + mobility It Begins with State Space Search!
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3 Brian Williams, Fall 10 5 Problem Solving as State Space Search • Problem Formulation (Modeling) – Problem solving as state space search • Formal Representation – Graphs and search trees • Reasoning Algorithms – Depth and breadth-first search Brian Williams, Fall 10 6 Most Agent Building Block Implementations Use Search Robust Operations: • Activity Planning • Diagnosis • Repair • Scheduling • Resource Allocation Mobility: • Path Planning • Localization • Map Building • Control Trajectory Design
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4 Brian Williams, Fall 10 7 Example: Outpost Logistics Planning Brian Williams, Fall 10 8 Early AI: What are the universal problem solving methods? Astronaut Goose Grain Fox Rover Can the astronaut get its supplies safely across a Lunar crevasse? ± Astronaut + 1 item allowed in the rover. ± Goose alone eats Grain ± Fox alone eats Goose Simple Trivial Image produced for NASA by John Frassanito and Associates.
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5 Brian Williams, Fall 10 9 Problem Solving as State Space Search Formulate Goal – State • Astronaut, Fox, Goose & Grain below crevasse. Formulate Problem – States • Astronaut, Fox, Goose & Grain above or below the crevasse. – Operators • Move: Astronaut drives rover and 1 or 0 items to other side of crevasse . – Initial State Generate Solution – Sequence of Operators (or States) • Move(goose,astronaut), Move(astronaut), . . . Brian Williams, Fall 10 10 Astronaut Goose Grain Fox Astronaut Goose Grain Fox Grain Fox Astronaut Goose Goose Grain Astronaut Fox Goose Fox Astronaut Grain Goose Grain Fox Astronaut
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6 Brian Williams, Fall 10 11 Astronaut Goose Grain Fox Grain Fox Astronaut Goose Astronaut Goose Grain Fox Goose Fox Astronaut Grain Astronaut Grain Fox Goose Astronaut Goose Grain
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MIT16_410F10_lec02 - Problem Solving as State Space Search...

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