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The seminal application of SRI's PRS was a monitoring and fault detection system for the reaction control system (RCS) on the NASA space shuttle. The RCS provides propulsive forces from a collection of jet thrusters and controls altitude of the space shuttle. A PRS-based fault diagnostic system was
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or belief–desire–intention framework for intelligent agents. Beliefs consist of what the agent believes to be true about the current state of the world, desires consist of the agent's goals, and intentions consist of the agent's current plans for achieving those goals. Furthermore, each of these
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machine and used multiple communicating instances of PRS. The system maintained over 1000 facts about the RCS, over 650 facts for the forward RCS alone and half of which are updated continuously during the mission. A version of the PRS was used to monitor the reaction control system on the
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The interpreter is responsible for maintaining beliefs about the world state, choosing which goals to attempt to achieve next, and choosing which knowledge area to apply in the current situation. How exactly these operations are performed might depend on domain-specific
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including navigational and simulated jet malfunction scenarios based on the space shuttle. Later applications included a network management monitor called the
Interactive Real-time Telecommunications Network Management System (IRTNMS) for
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systems that generate a complete plan at the beginning, and replan if unexpected things happen, PRS interleaves planning and doing actions in the world. At any point, the system might only have a partially specified plan for the future.
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SRI's PRS was developed for embedded application in dynamic and real-time environments. As such it specifically addressed the limitations of other contemporary control and reasoning architectures like
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M.P. Georgeff and A.L. Lansky. "A system for reasoning in dynamic domains: Fault diagnosis on the space shuttle" Technical Note 375, Artificial
Intelligence Center, SRI International, 1986.
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developed and tested using a simulator. It included over 100 KAs and over 25 meta level KAs. RCS specific KAs were written by space shuttle mission controllers. It was implemented on the
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just provides a model of what the states of the world are and how the agent's primitive actions affect them). Such a program, together with a PRS
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represented somewhere within the memory of the PRS agent at runtime, which is in contrast to purely reactive systems, such as the
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to be realized by the system as conditions over an interval of time on internal and external state descriptions (desires).
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650:" Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, Detroit (Michigan), August 1989.
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131:. The seminal application of the framework was a fault detection system for the reaction control system of the
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127:. Their framework was responsible for exploiting and popularizing the BDI model in software for control of an
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Technical Report, Artificial
Intelligence Center, Technical Report, SRI International, Menlo Park, CA, 1997
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185:(KAs) or plans that define sequences of low-level actions toward achieving a goal in specific situations.
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Rao, Anand S.; Michael P. Georgeff (1991). "Intelligent Real-Time
Network Management".
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that can perform complex tasks in dynamic environments. It is based on the notion of a
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A user application is predominately defined, and provided to a PRS system is a set of
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The following list the major implementations and extensions of the PRS architecture.
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that specifies how to do something, e.g., how to navigate down a corridor, or how to
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643:" Final Report – Phase 1, Artificial Intelligence Center, SRI International, 1988.
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Proceedings of the AAAI 2007 Spring
Symposium on Intentions in Intelligent Systems
214:. The following define the general requirements for the development of their PRS:
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that include those KAs that have been selected for current and eventual execution.
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Proceedings of the Sixth
National Conference on Artificial Intelligence (AAAI-87)
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629:" Technical Note 380, Artificial Intelligence Center, SRI International, 1987.
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for beliefs about the world, represented using first order predicate calculus.
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Reasoning and
Planning in Dynamic Domains: An Experiment with a Mobile Robot
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Proceedings of the sixth conference on
Artificial intelligence applications
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The system architecture of SRI's PRS includes the following components:
420:"Real-time reasoning: the monitoring and control of spacecraft systems"
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396:
496:"Reasoning about BDI Agents from a Programming Languages Perspective"
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Australian
Artificial Intelligence Institute, Technical Note 15
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through to the late 1990s, which led to the development of a
381:"An architecture for real-time reasoning and system control"
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132:
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Michael P. Georgeff, Amy L. Lansky, Marcel J. Schoppers. "
636:. Proceedings of the IEEE 74(10):1383–1398, IEEE Press.
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158:
417:
16:
Decision-making framework for artificial intelligence
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676:
An extension to PRS maintained by SRI International
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646:Michael P. Georgeff and François Félix Ingrand "
639:Georgeff, Michael P.; Ingrand, Francois Felix. "
648:Decision-Making in an Embedded Reasoning System
197:or inference mechanism that manages the system.
655:User Guide for the Procedural Reasoning System
531:"PRS, C-PRS, Propice, OpenPRS | FĂ©lix Ingrand"
695:
331:SRI Procedural Agent Realization Kit (SPARK)
140:Australian Artificial Intelligence Institute
119:during the 1980s, by many workers including
31:) is a framework for constructing real-time
138:. Development on this PRS continued at the
702:
688:
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242:handling of incomplete or inaccurate data
641:Research on procedural reasoning systems
379:Ingrand, F.; M. Georgeff; A Rao (1992).
345:Distributed multi-agent reasoning system
313:Distributed multi-agent reasoning system
157:
418:Georgeff, M. P.; F. F. Ingrand (1990).
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632:M. Georgeff, and A. L. Lansky (1987).
493:
437:Georgeff, M. P.; A. L. Lansky (1987).
355:Belief–desire–intention software model
224:procedural representation of knowledge
221:guaranteed reaction and response types
45:belief–desire–intention software model
683:
674:PRS-CL: A Procedural Reasoning System
304:OpenPRS (formerly C-PRS and Propice)
111:The PRS concept was developed by the
82:knowledge areas. Unlike traditional
54:. Each knowledge area is a piece of
146:implementation and extension called
230:reactive and goal-directed behavior
13:
616:
14:
1064:
1048:Agent-based programming languages
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439:"Reactive reasoning and planning"
236:reflective reasoning capabilities
162:Depiction of the PRS architecture
74:, is used to control the agent.
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451:Artificial Intelligence Center
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113:Artificial Intelligence Center
95:three components is typically
1:
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239:continuous embedded operation
227:handling of multiple problems
959:Constraint logic programming
875:Knowledge Interchange Format
832:Procedural reasoning systems
789:Expert systems for mortgages
784:Connectionist expert systems
7:
855:Attempto Controlled English
553:"Openprs - Openrobots Wiki"
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218:asynchronous event handling
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25:procedural reasoning system
10:
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1053:SRI International software
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1002:Preference-based planning
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888:
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802:
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248:modeling delayed feedback
1033:Knowledge representation
711:Knowledge representation
101:subsumption architecture
946:Constraint satisfaction
350:JACK Intelligent Agents
327:JACK Intelligent Agents
275:Space Shuttle Discovery
136:Space Shuttle Discovery
21:artificial intelligence
1038:Cognitive architecture
997:Partial-order planning
954:Constraint programming
494:Wobcke, W. R. (2007).
245:handling of transients
163:
125:François Félix Ingrand
880:Web Ontology Language
822:Deductive classifiers
761:Knowledge engineering
746:Model-based reasoning
736:Commonsense reasoning
661:A Match Made in Space
161:
123:, Amy L. Lansky, and
64:robotic architectures
1012:State space planning
992:Multi-agent planning
794:Legal expert systems
731:Case-based reasoning
634:Procedural knowledge
90:PRS is based on the
56:procedural knowledge
1043:Multi-agent systems
663:Spinoff, NASA, 2006
458:. pp. 198–204.
426:. pp. 198–204.
979:Automated planning
847:Ontology languages
817:Constraint solvers
592:"Index of /~spark"
578:"I.R.S. Downloads"
517:"I.R.S. Downloads"
280:PRS was tested on
233:focus of attention
164:
62:(in contrast with
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1019:
1007:Reactive planning
964:Local consistency
804:Reasoning systems
751:Inference engines
726:Backward chaining
456:SRI International
397:10.1109/64.180407
360:Intelligent agent
287:Telecom Australia
212:blackboard system
129:intelligent agent
117:SRI International
41:intelligent agent
33:reasoning systems
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756:Proof assistants
741:Forward chaining
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555:. Archived from
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537:. Archived from
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251:operator control
121:Michael Georgeff
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541:on 2007-11-11.
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559:on 2008-12-03
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561:. Retrieved
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391:(6): 34–44.
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265:3600 Series
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256:Applications
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194:
188:
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154:Architecture
110:
96:
89:
76:
51:
49:
28:
24:
18:
969:SMT solvers
535:www.laas.fr
385:IEEE Expert
195:Interpreter
84:AI planning
72:interpreter
60:plan a path
1027:Categories
563:2009-07-09
366:References
308:AgentSpeak
293:Extensions
189:Intentions
97:explicitly
80:meta-level
68:programmer
66:where the
43:using the
715:reasoning
475:CiteSeerX
263:Symbolics
606:"PRS-CL"
339:See also
210:and the
202:Features
171:Database
921:Prover9
916:Paradox
865:F-logic
405:2406220
334:PRS-CL
315:(dMARS)
301:UM-PRS
107:History
896:CARINE
477:
403:
319:GORITE
926:SPASS
911:Otter
906:Nqthm
870:FO(.)
779:CLIPS
499:(PDF)
442:(PDF)
401:S2CID
177:Goals
148:dMARS
860:CycL
713:and
323:JAM
272:NASA
267:LISP
133:NASA
23:, a
931:TPS
393:doi
144:C++
115:at
92:BDI
39:or
29:PRS
19:In
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936:Z3
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