03-chapt3

# 03-chapt3 - CSE 630 Goal based Agents and Uninformed Search...

This preview shows pages 1–13. Sign up to view the full content.

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: CSE 630: Goal based Agents and Uninformed Search Prof. Naeem Shareef Goal-based agent Choose action based on present + future Car Driving Agent - Problem-solving State: A tuple of values (variables or constants) that describe the current environment City locations – City name, latitude/longitude, … Agents current location Goal: A subset of state variables with specific values Agent’s location at the destination city Problem-solving Goals are specified in terms of the state variables Start State : Initial description Goal State : Any state in which the goal description is achieved Successor State : Next state that may follow from the current state State Space : The entire set of all possible states Problem-solving Operators: Actions + its effects Transition from one state to a successor state Drive from Arad to Sibiu Goal Test: Way to determine whether current state is a goal state Capabilities of the Agent Perceive state variables from environment Infer states using internal reasoning Assumes that it is successful when it takes an action The next state is known in advance Determine solution (state transitions from start state to a goal state) before taking any action Assumptions about the Environment Observability : Fully observable (All state variables are known) Deterministic : World is static and predictable Sequential : Access to all possible states Static : World does not change while agent is choosing an action Discrete : The state variables for the world are countable Behavior of the Agent Find single action or sequence of actions that lead to desirable states (goal states) of the world A search problem! Issues … Many goal states (only want to reach one of them) Many ways to reach a goal state Performance measure (P. E. A. S.) Implementation Driving in Romania: (a route-finding problem) State variables? Goal State Description? Actions? Costs? Path Cost Solution? Driving in Romania:(a route-finding problem) State variables? Agent location (city name or latitude/longitude) Goal State Description? Bucharest Atomic Action Drive(Oradea, Zerind) … effect location current = Zerind Cost: Distance to get there Solution? Sequence of drive actions Vacuum Agent State variables?...
View Full Document

{[ snackBarMessage ]}

### Page1 / 59

03-chapt3 - CSE 630 Goal based Agents and Uninformed Search...

This preview shows document pages 1 - 13. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online