CSC 8520 Spring Paula Matuszek

Slides:



Advertisements
Similar presentations
Planning II: Partial Order Planning
Advertisements

Planning Module THREE: Planning, Production Systems,Expert Systems, Uncertainty Dr M M Awais.
Module R2 CS450. Next Week R1 is due next Friday ▫Bring manuals in a binder - make sure to have a cover page with group number, module, and date. You.
1 CSC 8520 Spring Paula Matuszek CS 8520: Artificial Intelligence Final Notes Paula Matuszek Spring, 2013.
TWEAK solving the Sussman anomaly ON(A,B) ON(B,C) ON(C,A) ONTABLE(A) ONTABLE(B) CLEAR(C) CLEAR(B) ARMEMPTY STACK(A,B) STACK(B,C) Two step additions to.
Chapter 4 - Planning 4.1 State Space Planning 4.2 Partial Order Planning 4.3Planning in the Real World Part II: Methods of AI.
Planning Chapter 10.
Planning Planning is fundamental to “intelligent” behaviour. E.g.
All rights reserved ©L. Manevitz Lecture 61 Artificial Intelligence Planning System L. Manevitz.
Sussman anomaly - analysis The start state is given by: ON(C, A) ONTABLE(A) ONTABLE(B) ARMEMPTY The goal by: ON(A,B) ON(B,C) This immediately leads to.
Planning Russell and Norvig: Chapter 11 Slides adapted from: robotics.stanford.edu/~latombe/cs121/2003/ home.htm.
Artificial Intelligence II S. Russell and P. Norvig Artificial Intelligence: A Modern Approach Chapter 11: Planning.
1 CSC 8520 Spring Paula Matuszek On the syllabus page there are links to two Prolog programs: a simple Prolog planner and an ADT library. Download.
1 Chapter 4 State-Space Planning. 2 Motivation Nearly all planning procedures are search procedures Different planning procedures have different search.
Planning Some material adapted from slides by Tim Finin,Jean-Claude Latombe, Lise Getoor, and Marie desJardins.
1 Classical STRIPS Planning Alan Fern * * Based in part on slides by Daniel Weld.
EXAMPLE OF PARTIAL ORDER PLANNING. Action Recipes: Action: Stack(x,y) Prec: Clear(x) ^ Clear(y) ^ OnTable(x) Effect: ~Clear(y) ^ ~OnTable(x) ^ On(x,y)
CPSC 322 Introduction to Artificial Intelligence November 19, 2004.
CPSC 322 Introduction to Artificial Intelligence November 26, 2004.
1 Planning Adapted from Tim Finin, UMBC, Marie desJardins Some material adopted from notes by Andreas Geyer-Schulz and Chuck Dyer.
1 Lecture 12 example (from slides prepared by Prof. J. Rosenchein)
Intro to AI Fall 2002 © L. Joskowicz 1 Introduction to Artificial Intelligence LECTURE 12: Planning Motivation Search, theorem proving, and planning Situation.
1 Pertemuan 17 Planning Matakuliah: T0264/Intelijensia Semu Tahun: Juli 2006 Versi: 2/1.
Installing Hugs on Windows March 31, Installing Hugs Go to Click on the Hugs link under implementations.
PLANNING Partial order regression planning Temporal representation 1 Deductive planning in Logic Temporal representation 2.
An Introduction to Artificial Intelligence CE Chapter 11 – Planning Ramin Halavati In which we see how an agent can take.
1 07. The planning problem 2  Inputs: 1. A description of the world state 2. The goal state description 3. A set of actions  Output: A sequence of actions.
Ali Shahrokni Application Components Activities Services Content providers Broadcast receivers.
April 3, 2006AI: Chapter 11: Planning1 Artificial Intelligence Chapter 11: Planning Michael Scherger Department of Computer Science Kent State University.
22/11/04 AIPP Lecture 16: More Planning and Operators1 More Planning Artificial Intelligence Programming in Prolog.
Chapter 7 Stacks. © 2004 Pearson Addison-Wesley. All rights reserved 7-2 The Abstract Data Type: Developing an ADT During the Design of a Solution Specifications.
CS.462 Artificial Intelligence SOMCHAI THANGSATHITYANGKUL Lecture 07 : Planning.
CPS 270: Artificial Intelligence Planning Instructor: Vincent Conitzer.
1 Search vs. planning Situation calculus STRIPS operators Search vs. planning Situation calculus STRIPS operators.
Exercise Your your Library ® RefWorks: Advanced November 21, 2006.
PLANNING He whose undertakings are all devoid of plan and desire for results, and whose actions are burnt by the fire of knowledge, him the sages call.
Linked List. Iterators Operation to find a link, deleting, and inserting before or after a specified link, also involve searching through the list to.
CPS 570: Artificial Intelligence Planning Instructor: Vincent Conitzer.
1 Chapter 16 Planning Methods. 2 Chapter 16 Contents (1) l STRIPS l STRIPS Implementation l Partial Order Planning l The Principle of Least Commitment.
AI Lecture 17 Planning Noémie Elhadad (substituting for Prof. McKeown)
1/16 Planning Chapter 11- Part1 Author: Vali Derhami.
CSC 9010 Spring, Paula Matuszek, Lillian Cassel 1 CS 9010: Semantic Web Protégé Lab Paula Matuszek Spring, 2006.
1 How to Install OpenGL u Software running under Microsoft Windows makes extensive use of "dynamic link libraries." A dynamic link library (DLL) is a set.
Intelligent Systems Planning.
April 3, 2006AI: Chapter 11: Planning1 Artificial Intelligence Chapter 11: Planning.
CS621: Artificial Intelligence Pushpak Bhattacharyya Computer Science and Engineering Department IIT Bombay Lecture 19: Hidden Markov Models.
1 Planning Some material adopted from notes by Andreas Geyer-Schulz and Chuck Dyer.
1 CS 132 Spring 2008 Chapter 1 Software Engineering Principles and C++ Classes.
CSC 143 P 1 CSC 143 Recursion [Chapter 5]. CSC 143 P 2 Recursion  A recursive definition is one which is defined in terms of itself  Example:  Compound.
Chapter 7 Stacks © 2006 Pearson Addison-Wesley. All rights reserved 7A-1.
Action Modeling with Graph-Based Version Spaces in Soar
An Introduction to Artificial Intelligence CE 40417
Planning Chapter 16.
L9. Planning Agents L7_exAnswer and explanation Review
Lecture 25 More Synchronized Data and Producer/Consumer Relationship
Introduction Contents Sungwook Yoon, Postdoctoral Research Associate
Chapter 1-4 CSc 212 Data Structures, Sec AB CCNY, Spring 2012
CS 8520: Artificial Intelligence
AI Planning.
Executing Runtime Checks (For Comp401 and Comp410)
L11. Planning Agents and STRIPS
Planning Chapter
CPSC 322 Introduction to Artificial Intelligence
CS344 : Introduction to Artificial Intelligence
Russell and Norvig: Chapter 11 CS121 – Winter 2003
L9. STRIPS Examples Recursive STRIPS Block world
CSCS-200 Data Structure and Algorithms
Prof. Pushpak Bhattacharyya, IIT Bombay
Chapter 7 © 2011 Pearson Addison-Wesley. All rights reserved.
CMPT 225 Lecture 7 – Stack.
Presentation transcript:

CSC 8520 Spring 2013. Paula Matuszek Lab Exercise 1 On the syllabus page there are links to two Prolog programs: a simple Prolog planner and an ADT library. Download them and consult planner.pl, which will in turn consult adts.pl. ?- consult('planner.pl'). % adts compiled 0.00 sec, 6,364 bytes % planner.pl compiled 0.00 sec, 11,456 bytes true. CSC 8520 Spring 2013. Paula Matuszek

CSC 8520 Spring 2013. Paula Matuszek Test that it is working by typing “test.” at the prompt. You should get a list of moves. ?- test. moves are pickup(a) putdown(a) pickup(b) stack(b, c) stack(a, b) true. ?- CSC 8520 Spring 2013. Paula Matuszek

CSC 8520 Spring 2013. Paula Matuszek Planner Planner is a very simple Prolog implementation of a planner using a STRIPS-like notation. A state is a list of conditions. A problem has an initial state and a goal state. For instance: the initial state for a blocks world might be: [handempty, ontable(b), ontable(c), on(a, b), clear(c), clear(a)] the goal state for the blocks world might be: [handempty, ontable(c), on(a,b), on(b, c), clear(a)] CSC 8520 Spring 2013. Paula Matuszek

CSC 8520 Spring 2013. Paula Matuszek Moves A move is an action, consisting of a name, a list of preconditions, and an effect list of changes. Moves are included in the Prolog file. For example: move(pickup(X), % move name [handempty, clear(X), on(X, Y)], % preconditions [del(handempty), del(clear(X)), % list of conditions del(on(X, Y)), add(clear(Y)), % to be added and add(holding(X))]). % deleted CSC 8520 Spring 2013. Paula Matuszek

CSC 8520 Spring 2013. Paula Matuszek plan plan takes a current state, a goal state, a list of states which have already been reached (Been_list), and a list of moves which have already been carried out. It then checks to see if the current state = goal state. If so, print out list of moves. finds an applicable move does the adds and deletes checks to be sure we haven’t already been there adds the current state to the list of states and the current move to the list of moves recurs. CSC 8520 Spring 2013. Paula Matuszek

CSC 8520 Spring 2013. Paula Matuszek Running it go takes an initial state and a goal state it invokes plan with current state = initial state goal state = goal state Been_list = initial state Moves list empty. test is just there to give a way to test it, using the blocks world. CSC 8520 Spring 2013. Paula Matuszek 6

CSC 8520 Spring 2013. Paula Matuszek Spare tire problem Problem: you have a flat. Develop a plan to fix it. Initial condition is that the flat is on the axle and the spare is in the trunk. Goal condition is that the flat is in the trunk and the spare is on the axle. Some possible actions include removing something from something, installing something in something. Some possible conditions include at(a,b) and clear(axle) CSC 8520 Spring 2013. Paula Matuszek

CSC 8520 Spring 2013. Paula Matuszek Lab exercise 2. Develop the appropriate initial state, goal state and move definitions for the Spare Tire Problem. Add to planner.pl your moves and a new predicate test2 which solves this problem. CSC 8520 Spring 2013. Paula Matuszek