Outline for 4/23

4/23/98


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Table of Contents

Outline for 4/23

Logistics

Course Topics by Week

Agent vs. Environment

Two Approaches to Agent Control

Planner

Input Representation

Representing Actions

How Represent Actions?

STRIPS Actions

Action Schemata

Planning as Search

Forward-Chaining World-Space Search

Backward-Chaining World-Space Search

Planning as Search 2

Plan-Space Search

Planning as Search 3

Planning Graph

Constructing the planning graph…

Mutual Exclusion

Graphplan

Searching for a Solution

Dinner Date

Planning Graph

Are there any exclusions?

Do we have a solution?

Extend the Planning Graph

One (of 4) possibilities

Summary Planning

Outline

Immobile Robots Example 2: Cassini Saturn Mission

Solution: Part 1 Model-based Programming

Solution: Part 2 Model-based Deductive Executive

Solution: Part 3 Risc-like Best-first, Deductive Kernel

Consider a sub family of model-based optimal controllers where...

A family of increasingly powerful deductive model-based optimal controllers

Specifying a valve

Mode identification + reconfiguration

Example: Cassini propulsion system

MI/MR as combinatorial optimization

Generic LTMS interface

Using the LTMS in MI and MR

Outline

Plain Propositional Logic

Transition systems

Markov models

Concurrent transition systems

Trajectories of concurrent transition systems

Transition system models

Specifying transition systems

Specifying a valve transition system

Valve transition system (cont.)

Configuration Manager

Mode Identification

Characterizing MI

Characterizing MI

Mode Reconfiguration: Reachability in the next state

Characterizing MR

Characterizing MR

Statistically Optimal Configuration Management

MI and MR as combinatorial optimization

Outline

Limitations of Model-based Configuration Management

Limitations (cont.)

Model-based Reactive Executive

Model-based Reactive Control System < S, ???????

Why plan myopically by assuming the most likely state is correct?

How does MR search efficiently over the set of feasible target states?

Model-based Reactive Planning Relation to STRIPS planning?

Comparing MRP and STRIPS

How Burton Achieves Reactivity

Driver Valve Example

Model Compilation

Compile by Generating Prime Implicates

Simplifying to Strips

Simplifying to Strips (cont.)

Reasons Search is Needed

Exploiting Causality to Avoid Threats

Exploiting Causality to Avoid Threats

Avoiding Clobbering Sibling Goals

Avoiding Clobbering Sibling Goals

Burton: Online Algorithm (partial)

Exploiting Safety

Avoiding Deadend (Sub) Goals

Defining Reversibility

Reversibility Labeling Algorithm

Burton: Online Algorithm

Incorporating Repair Actions

Eliminating Cost of Finding Transition Paths: Generating Concurrent Policies

Burton computes next action (step 1)

Burton computes next action (step 2)

Failure occurs during plan execution Burton computes next action - step 3

Burton computes next action (step 4)

Complexity: Constant Average Cost

Outline

Autonomous System Coding Challenge

Solution: Part 1 Model-based Programming

Solution: Part 2 Model-based Deductive Executive

Solution: Part 3 Risc-like Best-first, Deductive Kernel

Concurrent Transition Systems

Representation with Modal Logic

MI/MR as combinatorial optimization

Model-based Reactive Executive

How Burton Achieves Reactivity

Demonstration of Model-based Autonomy Capabilities

Future: Systems that Model & Adapt

Future: Systems that Seek Information

Future: Systems that Anticipate

Author: weld

Email: weld@cs.washington.edu

Other information:
CSE 592, Lecture 4

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