l3a_bw_uninf_sch

l3a_bw_uninf_sch - Problem Solving as State Space Search...

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Problem Solving as State Space Search Brian C.Williams 16.410-13 Se ssion 3 Slides adapted from: 6.034 Tomas Lozano Perez, Russell and Norvig AIMA Brian Wil iams, Fal 05 1 Assignments Remember: Problem Set #1: Simple Scheme and Search Out today, due Se ssion 4 . • Reading: – Solving problems by searching: AIMA Ch. 3 Brian Wil iams, Fal 05 2 Course Objective 1: Agent Architectures To understand the major types of agents and common architectures used to develop agents. Mission-oriented Agents Self-repairing Agents Mobile Agents Agile Agents Communicating Agents Brian Wil iams, Fal 05 3 Brian Wil iams, Fal 05 4 Plan Execute Monitor & Diagnosis Locate in World Plan Routes Map Maneuver and Track Communicate and Interpret Course Objective 1: Agent Architectures Course Objective 2: Principles of Agents 16.410/13: To learn the modeling and algorithmic building blocks for creating reasoning and learning agents: 1. To formulate reasoning problems in an appropriate formal representation. 2. To describe, analyze and demonstrate the application of reasoning algorithms to solve these problem formulations. Brian Wil iams, Fal 05 5 Agent Building Blocks • Activity Planning • Path Planning • Execution/Monitoring • Localization • Diagnosis • Map Building • Repair • Trajectory Design • Scheduling • Policy Construction Resource Allocation Most reasoning problems, like these, may be formulated as state space search. Brian Wil iams, Fal 05 6 1
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Course Objective 3: Implementing Agents 16.413: To appreciate the challenges of building a state of the art autonomous explorer: Fall 03: • Mars Exploration Rover shadow mode demonstration. Fall 04: • Gnu Robot competition. Fall 05: • Model-based autonomy toolbox • The virtual solar system • Stay tuned for more. Brian Wil iams, Fal 05 7 Brian Wil iams, Fal 05 8 Complex missions must carefully: Most AI problems, like these, may be formulated as state space search. • Plan complex sequences of actions • Schedule actions • Allocate tight resources • Monitor and diagnose behavior • Repair or reconfigure hardware. Courtesy of Kanna Rajan, NASA Ames. Used with permission. Outline • Problem Formulation – Problem solving as state space search • Mathematical Model – Graphs and search trees • Reasoning Algorithms – Depth and breadth-first search Brian Wil iams, Fal 05 9 Problem Solving as State Space Search • Formulate Goal – State • Astronaut, Fox, Goose & Grain across river • Formulate Problem – States Location of Astronaut, Fox, Goose & Grain at top or bottom river bank – Operators Astronaut drives rover and 1 or 0 items to other bank. • Generate Solution – Sequence of Operators (or States) • Move(goose,astronaut), Move(astronaut), . . . Brian Wil iams, Fal 05 11 Brian Wil iams, Fal 05 10 Early AI: What are the universal problem solving methods?
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l3a_bw_uninf_sch - Problem Solving as State Space Search...

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