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In Defense of Reaction Plans as Caches
Universal plans address the tension between reasoned behavior and timely response by caching reactions for classes of possible situations. This technique reduces the average time required to select a response at the expense of the space required to store the cache-the classic time-space trade-off. In his article, Matthew Ginsberg argues from the time extreme and against the space extreme. Although I find both extremes undesirable, I defend an increase in space consumption.
Review of Knowledge-Based Systems
The vendors Based Systems, 355 pp., and Volume 2, techniques. They are interesting of knowledge-based-systems development Knowledge Acquisition Tools for Expert and informative, particularly tools, for example, Inference, Systems, 343 pp., Academic Press, San "Generalization and Noise" by Y. IntelliCorp, Aion, AI Corp., and IBM, Diego, California, 1988), edited by B. Kodratoff and M. Manango, which would do well to pay heed to these R. Gaines and J. H. Boose, is an excellent discusses symbolic and numeric rule books because they point the way to collection of papers useful to both induction.
Universal Planning: An (Almost) Universally Bad Idea
Several authors have recently suggested that a possible approach to planning in uncertain domains is to analyze all possible situations beforehand and then store information about what to do in each. The result is that a system can simply use its sensors to examine its domain and then decide what to do by finding its current situation in some sort of a table. The purpose of this article is to argue that even if the compile-time costs of the analysis are ignored, the size of the table must, in general, grow exponentially with the complexity of the domain. This growth makes it unlikely that this approach to planning will be able to deal with problems of an interesting size; one really needs the ability to do some amount of inference at run time. In other words, an effective approach to acting in uncertain domains cannot be to look and then leap; it must always be to look, to think, and only then to leap.
Penguins Can Make Cake
Since this article is a counting argument, the conclusion time, a number of alternatives have been proposed. Presumably, in realistic cases, the Universally Bad Idea," analyzes one such number of sensors is large enough that a universal alternative, Marcel Schoppers's universal plan could not fit in your head. He also extends this analysis to a There are two reasons not to be concerned number of other systems, including Pengi about this apparent problem. They involve (A gre and Chapman 1987), which was structure and state, designed by Phil Agre and myself. Ginsberg's criticisms of universal plans rest Using universal plans, he says, is infeasible because their size is exponential in the number of possible domain states. Representing such a plan is infeasible in even quite small realistic domains. I'm sympathetic to such arguments, having made similar ones to the effect that classical planning is infeasible (Agre and Chapman 1988; Chapman 1987b). I don't understand the details of Schoppers's ideas, so I'm not sure whether this critique of universal plans per se is correct. However, I show that these arguments do not extend to Pengi. Ginsberg calls Pengi an approximate universal plan, by which he means it is like a universal plan except that it does not correctly specify what to do in every situation. However, Pengi's operation involves no plans, universal or approximate, and Pengi and universal plans, although they share some motivations, have little to do with each other as technical proposals. Ginsberg suggests number of its inputs. Pengi-like system, computation in the number of pixels or that, Blockhead, which efficiently solves the fruitcake on the average, business data processing takes problem; the way it solves it elucidates exponential work in the number of records. They have a lot The fruitcake problem is to stack a set of of structure to them, and this structure can be labeled blocks so that they spell the word exploited to exponentially reduce the computation's fruitcake. What is apparently difficult about size. I show impossible under the rules of the domain, Blockhead solving a problem involving 45 and the remainder can be categorized relatively blocks in which there are 45! 1056 configurations, cheaply to permit abstraction and There is every in every configuration, so it is not by reason to think that this same structure is approximation that it succeeds. Indeed, Ginsberg makes this and a central system. The [planning couldn't work if] there were no visual system is a small subset of Pengi's rhyme or reason to things."
Knowledge-Based System Applications in Engineering Design: Research at MIT
Sriram, Duvvuru, Stephanopoulos, George, Logcher, Robert, Gossard, David, Groleau, Nicholas, Serrano, David, Navinchandra, Dundee
Advances in computer hardware and software and engineering methodologies in the 1960s and 1970s led to an increased use of computers by engineers. In design, this use has been limited almost exclusively to algorithmic solutions such as finite-element methods and circuit simulators. However, a number of problems encountered in design are not amenable to purely algorithmic solutions. These problems are often ill structured (the term ill-structured problems is used here to denote problems that do not have a clearly defined algorithmic solution), and an experienced engineer deals with them using judgment and experience. AI techniques, in particular the knowledge-based system (KBS) technology, offer a methodology to solve these ill-structured design problems. In this article, we describe several research projects that utilize KBS techniques for design automation. These projects are (1) the Criteria Yielding, Consistent Labeling with Optimization and Precedents-Based System (CYCLOPS), which generates innovative designs by using a three-stage process: normal search, exploration, and adaptation; (2) the Concept Generator (CONGEN), which is a domain independent framework for conceptual or preliminary design; (3) Constraint Manager (CONMAN), which is a constraint-management system that performs the evaluation and consistency maintenance of constraints arising in design; (4) the distributed and integrated environment for computer-aided engineering (DICE), which facilitates coordination, communication, and control during the entire design and construction/manu-facturing phases; and (5) DESIGN-KIT, which can be envisioned as a new generation of computer-aided engineering environment for process-engineering applications.
On Interface Requirements for Expert Systems
The user interface to an expert system shares many design objectives and methods with the interface to a computer system of any sort. Nevertheless, significant aspects of behavior and user expectation are peculiar to expert systems and their users. These considerations are discussed here with examples from an actual system. Guidelines for the behavior of expert systems and the responsibility of designers to their users are proposed. Simplicity is highly recommended. Entia non sunt multiplicanda praete necessitatem.
The Power of Physical Representations
Akman, Varol, Hagen, Paul J. W. ten
Commonsense reasoning about the physical world, as exemplified by "Iron sinks in water" or "If a ball is dropped it gains speed," will be indispensable in future programs. We argue that to make such predictions (namely, envisioning), programs should use abstract entities (such as the gravitational field), principles (such as the principle of superposition), and laws (such as the conservation of energy) of physics for representation and reasoning. These arguments are in accord with a recent study in physics instruction where expert problem solving is related to the construction of physical representations that contain fictitious, imagined entities such as forces and momenta (Larkin 1983). We give several examples showing the power of physical representations.
Current Issues in Natural Language Generation: An Overview of the AAAI Workshop on Text Planning and Realization
Hovy, Eduard H., McDonald, David D., Young, Sheryl R.
Largely from this Traditionally, systems that automatically and realization--was widely experience, we came to understand generate natural language have deemed more convenient than accurate: the sorts of tasks that a text planner been conceived as consisting of two The components of a generator has to perform: determining which principal components: a text planner should be able to communicate at elements to say, coherently structuring and a realization grammar. Recent any level where their information is the input elements, building advances in the art, especially in the applicable.