AIList-REQUEST@SRI-AI.ARPA (AIList Moderator Kenneth Laws) (10/07/85)
AIList Digest Monday, 7 Oct 1985 Volume 3 : Issue 136 Today's Topics: Seminars - Higher-Order Logic Features in Prolog (UPenn) & Cognitive Science and Computers (UCB) & The Programmer's Apprentice: KBEmacs (CMU) & Belief, Awareness, and Limited Reasoning (SU) & Planning Under Uncertainty using Simulation (SU) & Aggregation in Qualitative Simulation (MIT) & Conflict in Problem Solving (MIT) & Introspection (SU) & Compact Lisp Machine (SMU), Seminar Series - IBM Yorktown Projects (Rutgers) ---------------------------------------------------------------------- Date: Sun, 29 Sep 85 10:44 EDT From: Dale Miller <Dale%upenn.csnet@CSNET-RELAY.ARPA> Subject: Seminar - Higher-Order Logic Features in Prolog (UPenn) [Forwarded from the Prolog Digest by Restivo@SU-SCORE.] A student of mine is holding a seminar at the University of Pennsylvania that might be of interest to the Prolog bboard readers. -Dale Miller Joint Mathematics / Computer Science LOGIC COLLOQUIUM Introducing Higher-Order Logic Features into Prolog Gopalan Nadathur Monday 30th September 1985 4:40 p.m., DRL 4E17 This talk reports work being undertaken towards a doctoral dissertation under the supervision of Prof. Dale Miller. This work is motivated by a desire to examine whether certain features afforded by higher-order logics are useful in a computational setting. In this talk we shall present a language that is similar to that of Horn Clauses of first-order logic except that first-order terms are now replaced by typed lambda-calculus terms. We shall discuss a theorem-prover based on higher-order unification for this logic. We shall also attempt to motivate the usefulness of this language for specifying and performing computations. We are interested in extending this language by permitting suitably restricted occurrences of predicate variables, and we shall conclude our talk by a brief discussion of the issues involved in doing so. ------------------------------ Date: Wed, 2 Oct 85 12:46:31 PDT From: admin@ucbcogsci.Berkeley.EDU (Cognitive Science Program) Subject: Seminar - Cognitive Science and Computers (UCB) BERKELEY COGNITIVE SCIENCE PROGRAM Fall 1985 Cognitive Science Seminar -- IDS 237A TIME: Tuesday, October 8, 11:00 - 12:30 PLACE 240 Bechtel Engineering Center DISCUSSION: 12:30 - 1:30 in 200 Building T-4 SPEAKER: Terry Winograd, Computer Science, Stanford University TITLE: "What Can Cognitive Science Tell Us About Computers?" Much work in cognitive science rests on the assumption that there is a common form of "information processing" that under- lies human thought and language and that also corresponds to the ways we can program digital computers. The theory should then be valid both for explaining the functioning of the machines (at whatever level of "intelligence") and for under- standing how they can be integrated into human situations and activities. I will argue that theories like those of current cognitive science are based on a "rationalistic" tradition, which is appropriate for describing the mechanics of machine operation, but is inadequate for understanding human cognitive activity and misleading as a guide to the design and application of computer technology. The emphasis will be on looking at alternatives to this tradition, as a starting point for under- standing what computers really can do. ------------------------------ Date: 1 Oct 1985 1410-EDT From: Sylvia Brahm <BRAHM@C.CS.CMU.EDU> Subject: Seminar - The Programmer's Apprentice: KBEmacs (CMU) SPEAKER: Richard C. Waters (AIL, MIT) TOPIC: The Programmer's Apprentice: A Session with KBEmacs WHEN: Friday, October 18, 1985 WHERE: Wean Hall 4605 TIME: 1:30 P.M. The Knowledge-Based Editor in Emacs (KBEmacs) is the current demonstra- tion system implemented as part of the Programmer's Apprentice project. KBEmacs is capable of acting as a semi-expert assistant to a person who is writing a program -- taking over some parts of the programming task. Using KBEmacs, it is possible to construct a program by issuing a series of high level commands. This series of commands can be as much as an order of magnitude shorter than the program it describes. KBEmacs is capable of operating on Ada and Lisp programs of realistic size and complexity. Although KBEmacs is neither fast enough nor robust enough to be considered a true prototype, both of these problems could be overcome if the system were to be reimplemented. ------------------------------ Date: Tue 1 Oct 85 08:40:19-PDT From: Anne Richardson <RICHARDSON@SU-SCORE.ARPA> Subject: Seminar - Belief, Awareness, and Limited Reasoning (SU) DAY October 1, 1985 EVENT Computer Science Colloquium PLACE Skilling Auditorium TIME 4:15 TITLE Belief, Awareness, and Limited Reasoning PERSON Dr. Joe Halpern FROM IBM Corporation BELIEF, AWARENESS, AND LIMITED REASONING Classical possible-worlds models for knowledge and belief suffer from the problem of logical omniscience: agents know all tautologies and their knowledge is closed under logical consequence. This unfortunately is not a very accurate account of how people operate! We review possible-worlds semantics, and then go on to introduce three approaches towards solving the problem of logical omniscience. In particular, in our logics, the set of beliefs of an agent does not necessarily contain all valid formulas. One of our logics deals explicitly with awareness, where, roughly speaking, it is necessary to be aware of a concept before one can have beliefs about it, while another gives a model of local reasoning, where an agent is viewed as a society of minds, each with its own cluster of beliefs, which may contradict each other. The talk will be completely self-contained. ------------------------------ Date: Tue 1 Oct 85 14:27:13-PDT From: Alison Grant <GRANT@SUMEX-AIM.ARPA> Subject: Seminar - Planning Under Uncertainty using Simulation (SU) Medical Information Sciences Colloquium Thursday, October 3, 1985 Stanford University Medical Center Room M-114 1:15-2:15 P.M. Speaker: Curt Langlotz, MIS Program Title: Planning under uncertainty using probabilistic and symbolic simulation Artificial intelligence research has largely concentrated on solving two kinds of planning problems: (1) problems for which there is certainty about the consequences of action and for which the planning goals can be met completely (e.g., robot movement between rooms in a building), and (2) problems for which explicit guidelines exist for the construction of plans (e.g., the ONCOCIN, MOLGEN, and ATTENDING programs). However, many planning problems are characterized by a lack of explicit plan construction guidelines, goals that are difficult to satisfy completely, and actions whose consequences cannot be predicted with certainty. This talk will describe an architecture for planning in such situations and will outline the motivations behind its design. One key component of this new architecture is the ability to predict the consequences of plans. A simulation architecture is currently under development to make these predictions. It will also be described, along with the motivations for rejecting existing simulation techniques (both qualitative and deterministic) in the domain of cancer therapy planning. ------------------------------ Date: Mon, 30 Sep 1985 16:21 EDT From: Peter de Jong <DEJONG%MIT-OZ at MIT-MC.ARPA> Reply-to: Cog-Sci-Request%MIT-OZ Subject: Seminar - Aggregation in Qualitative Simulation (MIT) [Forwarded from the MIT bboard by SASW@MIT-MC.] Thursday 3, October 4:00pm Room: NE43- 8th floor Playroom The Artificial Intelligence Lab Revolving Seminar Series "The Use of Aggregation in Qualitative Simulation" Daniel S. Weld MIT AI Lab. I introduce a technique called aggregation which has several applications to the problem of qualitative simulation and envisioning: - It can simplify reasoning by dynamically creating more abstract process descriptions of the types of change occurring in a system. - It can enable the application of powerful continuous analytic techniques such as limit analysis to systems whose descriptions include discrete processes. - It can direct the reformulation of quantities to more abstract representations. Aggregation works by searching the simulation history structure to find cycles of repeating processes. Once cycles have been detected, a more abstract continuous process, equivalent to the net effect of the cycle, is created. Analysis now proceeds on the continuous process. Aggregation correctly handles cycles that contain other cycles. A program called PEPTIDE has been written to test these ideas in the domain of molecular genetics. Paper tests have also been done in the domains of digital electronics and xerography. ------------------------------ Date: Mon 30 Sep 85 18:18:03-EDT From: Michael Eisenberg <DUCK%MIT-OZ at MIT-MC.ARPA> Subject: Seminar - Conflict in Problem Solving (MIT) [Forwarded from the MIT bboard by Laws@SRI-AI.] Andre Boder is scheduled to give a talk at the next ideas seminar, TOMORROW, Tuesday Oct. 1, at 4:30. The talk is scheduled to be held at the 3rd floor conference room in NE43. Title: What Is a Conflict in Problem Solving? I will address the question of why people have difficulty in problem-solving, arguing that in most cases, a conflict between incompatible ideas may be evoked. The conjecture is based on the analysis of familiar-schemes brought to bear in the problem. I will show that the relation between these schemes may generate incompatible representations of the same situation. Conflicts result from difficulty in reducing these incompatibilities. ------------------------------ Date: Thu 3 Oct 85 07:50:26-PDT From: Ana Haunga <HAUNGA@SUMEX-AIM.ARPA> Subject: Seminar - Introspection (SU) SIGLUNCH, Friday, October 4, Chemistry Gazebo, 12:05-1:00. Introspection Michael R. Genesereth Logic Group Knowledge Systems Laboratory Stanford University Abstract: Introspection is a significant part of human mental activity. We introspect whenever we think about how to solve problem, whenever we decide what information we need to solve a problem, whenever we decide that a problem is unsolvable. By its nature, the process of introspection involves both descriptive and prescriptive metaknowledge. Over the past years, logicians and AI researchers have devoted considerable attention to autoepistemic sentences (involving terms like KNOW). By comparison, little attention has been paid to prescriptive metaknowledge (involving terms like OUGHT). This talk introduces a semantics for such knowledge in the form of constraints on the process of problem solving. It demonstrates the computational advantages of introspection, and analyzes the computational fidelity and cost of various introspective architectures. Finally, it discusses the potential for practical application in logic programming and building expert systems. ------------------------------ Date: 3 Oct 1985 09:08-CST From: leff%smu.csnet@CSNET-RELAY.ARPA Subject: Seminar - Compact Lisp Machine (SMU) Speaker: Lawerence E. Gene Matthews Associate Director of the Computer Science Laboratory Texas Instruments, Dallas Date: Wednesday, October 16, 1985 Time: 11:30 AM Luncheon 12:15 Program Place: Richardson Hilton, SW corner of N. Central Expressway & Campbell The Compact LISP Machine (CLM) development program is the first of several DARPA programs intended to provide embedded symbolic computing capbilities for government applications. As one of many contacts funded under the Strategic Computing Program the CLM will provide a ruggedized symbolic computer capability for insertion of AI and robotics technology in awide range of applications. A description of the four-module CLM system architecture is presented. Starting with the CLM development goals, a brief system overview and discussion of advanced software development and maintenance tools are covered. System and module packaging are described including options available beyond the scope of the current contract. Each of the four modules under development are described starting with the CPU module, which contains the 40 Mhz VLSI CPU chip, and its companion map/cache module. The module developed for providing physical memory is described followed by a discussion of the Multibus I/O module which supports communication between the high performance system bus and Multibus I. The VLSI LISP processor chip is next described with a simplified block diagram and packaging information. Finally, some information on preliminary predicted performance is covered. Luncheon reservations 995-4440 Monday October 14 $7.00 ------------------------------ Date: Wed, 11 Sep 85 13:43:21 EDT From: Chidanand Apte <Apte.Yktvmv%ibm-sj.csnet@csnet-relay.arpa> Subject: Seminar Series - IBM Yorktown Projects (Rutgers) [Forwarded from the Rutgers BBoard by Laws@SRI-AI.] IBM talks at Rutgers-IBM AI exchange seminar, 10th Oct., Hill Center. Members of IBM Research from the T.J. Watson Research Center will be presenting six talks at the 3rd annual Rutgers-IBM AI exchange seminar, on 10th October 1985, at the Rutgers Computer Science dept. Preliminary titles and abstracts: "A representation for complex physical domains" Sanjaya Addanki We are exploring a system, called PROMPT, that will be capable of reasoning from first principles and high level knowledge in complex, physical domains. Such problem-solving calls for a representation that will support the different analyses techniques required (e.g. differential, asymptotic, perturbation etc.). Efficiency considerations require that the representation also support heuristic control of reasoning techniques. This talk lays the ground work for our effort by briefly describing the ontology and the representation scheme of PROMPT. Our ontology allows reasoning about multiple pasts and different happenings in the same space-time. The ontology provides important distinctions between materials, objects, bulk and distributed abstractions among physical entities. We organize world knowledge into "prototypes" that are used to focus the reasoning process. Problem-solving involves reasoning with and modifying prototypes. "YES/FAME/IDV: An initial approach to a planning consultant for financial marketing problems" Chidanand Apte/ Jim Griesmer/ John Kastner/ Yoshio Tozawa The YES/FAME (Yorktown Expert Systems for Financial and Marketing Expertise) project is investigating interactive consultants to aid in the financial marketing of computing technology. Significant expertise seems to be required in the preparation of a recommendation to a customer of a technical solution that meets his computing requirements over a period of time, coupled with a plan for acquiring this technology under financial terms and conditions that best suit the customer's needs and concerns. Expertise is also required in generating a convincing financial argument that will enable the "selling" of this plan. We present in this talk an overview of an initial demonstration version (YES/FAME/IDV) of a knowledge based system that illustrates these capabilities for a small subset of the overall problem. "Logical extensions of logic programming based on intuitionistic logic" Seif Haridi Logic Programming is widely known as programming using Horn clauses. We extend this paradigm to handle more general relations than Horn clauses. Based on principles from first order intuitionistic (constructive) logic we show a much more expressive language with a complete execution mechanism that is able to handle general first order queries, iterative and recursive statements, and positive and negative queries with equal strength. The language has Horn clauses as a subset, and its interpreter behaves as efficient as a Horn clause (PROLOG) interpreter on that subset. "PLNLP: The programming language for natural language processing" George Heidorn This talk describes research being done at Yorktown to provide advanced tools for building knowledge-based systems that involve a large amount of natural language processing. PLNLP is a programming language based on the augmented phrase structure grammar formalism that is particularly well-suited for specifying the processing of natural language text. A large, broad-coverage English grammar has been written in PLNLP, and implementations in LISP/VM and PL.8 are currently being used in applications doing text-critiquing, machine translation, and speech synthesis. One of these systems, CRITIQUE, will be used as a concrete illustration of the power of the language. "YSCOPE: A shell with domain knowledge for solving computer performance problems" Joseph Hellerstein Solving computer-performance problems requires two types of knowledge: knowledge of the computer system and insights from queueing theory. We describe the Yorktown Shell for Computer-Performance Experts (YSCOPE) which is a special-purpose shell that incorporates a knowledge of queueing theory to facilitate building computer-performance expert systems. "Interactive classification in knowledge representations" Eric Mays A classifier for a structured representation language allows semi-automatic maintenance of a knowledge base. However, problems, such as detecting and recovering from inconsistencies, arise when editing a KB which has been updated by classifier operations. This talk will address preliminary investigations along these lines. ------------------------------ End of AIList Digest ********************
pdg@ihdev.UUCP (P. D. Guthrie) (10/08/85)
I'm interested in some information about KBEmacs, then Knowledge Based Emacs that I have heard about. Specifically, I would like information about current implementations, powers, and limitations, for instance : how much of what it does is merely a function of a syntax editor (interactive syntax checker), compared to actual programming aid. Any leads to knowledgable people, papers (even in obscure journals - we have a fantastc technical library here!) or PD sources would be appreciated. Please mail directly, and I will post a summary - assuming of course I get enough of a response to summarize about! Paul Guthrie ihnp4!ihdev!pdg