Solving CsPs Solving CSPs involves some combination of 1. Constraint propagation eliminates values that cant be part of any solution 2. Search explores valid assignments Arc Consistency Arc consistency eliminates values of each variable domain that

autonomous gents Self-commanding Self-diagnosing IoHc-IO Self-repairing RECOVERY Commanded at Mission level Engineering level Monitors

Out line Propositional Satisfiability Propositional Clauses Backtrack search Unit Propagation DPLL: Unit Propagation Backtrack Search Characteristics of dPLl local search using GSAT Propositional Clauses

SlideGraph-based Plannings based on material from: Prof Dan Weld (Univ Washington)and Brian c。 Willams Prof. Maria Fox(Durham, UK) October 8th. 2003 16。410-13 autonomous Agents eIf-diagnosing Self-repairing RECOVERY Commanded at Mission level Engineering level Cor

September 24, 2003 Scheme Tutor notes In scheme tutor stick to r5rs scheme The Tutor uses SCM, not miT scheme Strategy: click\Check\button on initial code, in order to view test cases pt.24,2003 16410/16413 Even more scheme

Outline Objectives Agents and Their building Blocks Principles for building agents Modeling formalisms Algorithmic Principles Building an agent: The Mars Exploration rover

Markov Decision Processes and Reinforcement Learning · Motivation earning policies through reinforcement Q values

Robot Localization using SIR Take sample set X+_11 ll. iterate For each sample xt-1 1) Sample from p(X,1 X+1, a) 2) Attach importance weights

Assignment problem Persons and tasks connected by links Objective: Minimize total task time minutes Carburetor Manny 4 minutes Valves

Courtesy or Eric Feron and Sommer Gentry. Used with permission. Introduction to Linear Programming Eric Feron (updated Sommer Gentry)