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COMP 4640
Intelligent & Interactive Systems
Programs Supporting
Model - Based Reflex Agents
November 2008
Dr. Cheryl Seals
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Simple reflex agents
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Programs that support
Model - based Reflex Agents
Simple reflex agents
select precepts based on the
current perceptignoring the rest of the precepthistory
Example: Beetle
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Model-based reflex agents
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Programs that support
Model - based Reflex Agents
Most systems are based on condition-action rules
(i.e. situation-action rules, productions, or if-then rules)
(e.g. If car-in-front is braking then initiate-braking p46)
Model-Based Reflex Agents
Most effective way to keep track of the part of the
world it cant see now.
Maintain some internal state that depends onpercept history and thereby reflects at least someof the unobserved aspects of the current state (e.g.
using some type of variable).
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Production Based SystemsThe production rule paradigm originated in the field of AI with theexpert systems rule languages such as OPS5 (Brownston et al. 1985) condition action
An inference engine cycles through all the rules in the systemmatching the condition parts of the rules with data in working memory.
Of all the rules that match (the candidate set), one is selected usingsome conflict resolution policy and this selected rule is fired, that is,its action part is executed.
The action part may modify the working memory, possibly accordingto the matched data and the cycle continues until no more rulesmatch.
Rule based Rules have special ops:
Fire, which causes a rule to be triggeredEnable, which causes a rule to be activatedDisable, which causes a rule to be deactivated
Conflict resolution Break ties with Specification, Sequencing, Meta rules
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Production Based SystemsCLIPS
(CLanguage Integration Production System) Production system developed at NASAs Johnson space
center. Written in ANSI C instead of LISP CLIPS implements standard forward-chaining pattern-
matching algorithm CLIPS knowledge representation similar to OPS5 and ART
systems. Constructs
simple string fact assertion & retractionTemplatesIf-then rules (productions)Objects and instances
NASA uses clips in the following projects
Intelligent computer aided crew training, weatherforecasting, shuttle space planning, shuttlediagnostics, Mission Control Center (telemetry dataanalysis and diagnostics), flight assistance andcontrol
ART commercial expert system has many of thesame features as CLIPS
http://portal.acm.org/author_page.cfm?id=81100007064&coll=GUIDE&dl=GUIDE&trk=0&CFID=9450350&CFTOKEN=41813484http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=00176973http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=00176973http://portal.acm.org/author_page.cfm?id=81100007064&coll=GUIDE&dl=GUIDE&trk=0&CFID=9450350&CFTOKEN=418134848/3/2019 2.ModelBased Reflex Agent Intro
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Agent Based Systems
Systems to investigate
Stagecast CreatorTM (www.stagecast.com)
AgentsheetsTM (www.agentsheets.com)
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End User Programming with agentsStagecast Study Report:
We are attempting to create a cross-generational webbased learning community for middle school students,teachers, and seniors.
Learning community will design, construct, and discusssimulations of community issues.
Summary of results of formative evaluation with studentscreating simulation projects.
Proceedings of IEEE Visual Languages 2001, Rosson, Seals2001; CHI 2001; DIS 2002; NSF Research: NSF ITR 0091102.
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Based on a movie metaphorProgramming is facilitated by macro recorder to allowprogramming by demonstration
Behaviors are represented as a set of as a set of
productions or if-then rules
Stagecast Creator
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Procedure
Participants: 10 middle school students
Background survey
Performed in usability testing lab study with think aloud
protocol
Recorded critical incidents
Captured video, audio, and screen
Subjective questionnaire, knowledge survey,retrospective interview
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Visual Agent Programming
Spatial context and visual appearance arerequired elements in a rules precondition
Correct position and appearance are
preconditions for rules
If Precondition is satisfied, Then rule is fired.
Characters may have many instantiations
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Observations and Results
Duration 30-55 minutes Activity I
Duration 34-47 minutes Activity II
Most students were successful in modifying simulationsand adding new characters.
Usability satisfaction
Easy and fun to use
Would like to use it in their classes But needed more exposure to feel confident
No problems with drawing tools
Problems with tools for rule creation
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Issue Likely Cause
Directing input to the wrongwindow Too many similar-lookingwindows
Confused between rules andrule-actions lists
Lists that look similar but havedifferent meanings
Select wrong icon Multiple similar iconsInability to find rules or othercontent in window
Non-traditional method ofscrolling
Misunderstand spotlight andconcept of stretching it
Spotlight metaphor is notobvious or intuitive
Stagecast Usability Problems
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Practical metaphors for icons
Bigger Icons
Fewer layers of scaffoldingRelation between internal variables andvisual state of the simulation.
Role of visual context in rules Rules must match exact visual context, most
PBD system make rules to specific to be reused
Visual Programming Challenges
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End User Programming with agentsAgentSheets Study Report:
AgentSheets is a production basedvisual programming language whereend users create with directmanipulation techniques
Reports a study of teachers learningto build educational simulations ascurricula aids.
Summary of results of formative
evaluation to design agent basedproduction system for end usercreation of educational simulations.
Proceedings of IEEE VisualLanguages 2002, Seals 2002.
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Empirical Study Results
Need robust drawing tools
Objects should be important, not their spatiallocation
Flexible object size
Support for import of objects
Allow incremental testing
Increase the level of usability for noviceprogrammers
Platform independent implementation