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C. Forgy

Bio: C. Forgy is an academic researcher from Carnegie Mellon University. The author has contributed to research in topics: Natural language & Production (economics). The author has an hindex of 1, co-authored 2 publications receiving 174 citations.

Papers
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Proceedings Article
22 Aug 1977
TL;DR: Some of the issues that bear on the design of production system languages are explored and the adequacy of OPS is tried to show for its intended purpose.
Abstract: It has been claimed that production systems have several advantages over other representational schemes. These include the potential for general self-augmentation (i.e., learning of new behavior) and the ability to function in complex environments. The production system language, OPS, was implemented to test these claims. In this paper we explore some of the issues that bear on the design of production system languages and try to show the adequacy of OPS for its intended purpose.

173 citations

ReportDOI
22 Aug 1977
TL;DR: The Instructable Production System project is exploring the incremental growth properties of production systems by constructing a generally intelligent problem solving system by gradual (external) instruction by using means-ends analysis as the basic philosophy of both problem-solving and instruction.
Abstract: : The Instructable Production System project is exploring the incremental growth properties of production systems (PSs) by constructing a generally intelligent problem solving system by gradual (external) instruction. The present task domain is an abstract job shop, in which finished goods are made from raw materials. We start with a Kernel (a small PS of about 200 productions) which has the basic capabilities to grow by instruction: (1) process a restricted natural language; (2) form productions from its input; (3) impose PS control conventions on them; and (4) perform basic manipulations in its environment. (We take the basic computational and representational adequacy of PSs for AI programs as established.) This note presents some immediate difficulties that are expected. These derive from the instructional situation: (1) The instructor can observe the system in the environment and can communicate with it freely, but cannot examine its internal structure directly; (2) Interaction with system is in an external language, analogous to natural language; (3) The initiative for interaction is mixed; (4) Instruction may be on any topic--specific tasks, general properties of tasks, the language of communication, possible errors, how to plan and explore, etc; and (5) Knowledge and system structure gained through instruction accumulates over the life of the system. The current approach uses means-ends analysis as the basic philosophy of both problem-solving and instruction.

1 citations


Cited by
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Journal ArticleDOI
TL;DR: In this paper, a framework for skill acquisition is proposed that includes two major stages in the development of a cognitive skill: a declarative stage in which facts about the skill domain are interpreted and a procedural stage where the domain knowledge is directly embodied in procedures for performing the skill.
Abstract: A framework for skill acquisition is proposed that includes two major stages in the development of a cognitive skill: a declarative stage in which facts about the skill domain are interpreted and a procedural stage in which the domain knowledge is directly embodied in procedures for performing the skill. This general framework has been instantiated in the ACT system in which facts are encoded in a propositional network and procedures are encoded as productions. Knowledge compilation is the process by which the skill transits from the declarative stage to the procedural stage. It consists of the subprocesses of composition, which collapses sequences of productions into single productions, and proceduralization, which embeds factual knowledge into productions. Once proceduralized, further learning processes operate on the skill to make the productions more selective in their range of applications. These processes include generalization, discrimination, and strengthening of productions. Comparisons are made to similar concepts from past learning theories. How these learning mechanisms apply to produce the power law speedup in processing time with practice is discussed.

3,539 citations

Book
01 Aug 1993
TL;DR: SOAR, an implemented proposal for a foundation for a system capable of general intelligent behavior, is presented and its organizational principles, the system as currently implemented, and demonstrations of its capabilities are described.
Abstract: The ultimate goal of work in cognitive architecture is to provide the foundation for a system capable of general intelligent behavior. That is, the goal is to provide the underlying structure that would enable a system to perform the full range of cognitive tasks, employ the full range of problem solving methods and representations appropriate for the tasks, and learn about all aspects of the tasks and its performance on them. In this article we present SOAR, an implemented proposal for such an architecture. We describe its organizational principles, the system as currently implemented, and demonstrations of its capabilities.

2,429 citations

Journal ArticleDOI
TL;DR: SOAR as discussed by the authors is an implemented proposal for such an architecture, which is described in detail in the paper "SOAR: An Implementation of Cognitive Architecture for Artificial Intelligence" and demonstrated in the SOAR project.

2,328 citations

Journal ArticleDOI
TL;DR: The cognitive processes in a widely used, nonverbal test of analytic intelligence, the Raven Progressive Matrices Test (Raven, 1962), are analyzed in terms of which processes distinguish between higher scoring and lower scoring subjects and which processes are common to all subjects and all items on the test.
Abstract: The cognitive processes in a widely used, nonverbal test of analytic intelligence, the Raven Progressive Matrices Test (Raven, 1962), are analyzed in terms of which processes distinguish between higher scoring and lower scoring subjects and which processes are common to all subjects and all items on the test. The analysis is based on detailed performance characteristics, such as verbal protocols, eye-fixation patterns, and errors. The theory is expressed as a pair of computer simulation models that perform like the median or best college students in the sample. The processing characteristic common to all subjects is an incremental, reiterative strategy for encoding and inducing the regularities in each problem. The processes that distinguish among individuals are primarily the ability to induce abstract relations and the ability to dynamically manage a large set of problem-solving goals in working memory.

1,422 citations

Journal ArticleDOI
TL;DR: R1 is a program that configures VAX-11/780 computer systems and uses Match as its principal problem solving method; it has sufficient knowledge of the configuration domain and of the peculiarities of the various configuration constraints that at each step in the configuration process, it simply recognizes what to do.

1,001 citations