General problems in analyzing information in a probabilistic database are considered.

MRS stands for Meta-level Representation System. If your response to this is a knowing nod of understanding you can probably skip the first few chapters. In a sense, MRS is a computer language, in that one enters text in a designated syntax and it gets processed and produces answers (or not). But because MRS is also able to reason with the information you give it, the'program' you enter can be seen more as representing facts than specifying a process. The importance and utility of this difference will become clear.

Optimal construction of expert systems demands a powerful interactive environment for knowledge base management by knowledge engineers. Key requirements include techniques for (a) examining existing information, (b) adding new knowledge and editing preexisting data structures, and (c) examining dynamic internal system behavior to facilitate debugging during consideration of actual cases.

We have de,Jeloped an automated system for the design of laboratory experiments in molecular biology. The system uses a planning method known as skeletal plan refinement that attempts to emulate the human cognitive task of experiment design. This paper describes the theory, history, and implementation of the design system and illustrates its function in the domain of DNA cloning experiments.

A new method for automated planning, progressive refinement of skeletal plans, has been developed for the problem of experiment design in the domain of molecular biology. The method resulted from a study of the problem-solving behavior of scientists which showed that design usually consisted of lookup of abstracted plans followe6 by hierarchical plan-step refinement. The skeletal plan method has been implemented through two generations of problem-solving systems: the second generation involving a synthesis with the metaplanning approach of Stefik.

BBI, a blackboard system building architecture, ameliorates the Knowledge acquisition bottleneck with generic knowledge sources that learn control heuristics. Some learning knowledge sources replace the knowledge engineer, interacting directly with domain experts Others operate autonomously The paper presents a trace from the illustrative knowledge source. Understand-Preference, running in PROTEAN, a blackboard system for elucidating protein structure Understand-Preference is triggered when a domain expert overrides one of BBI s scheduling recommendations. It identifies and encodes the heuristic underlying the expert s scheduling decision. The trace illustrates how learning knowledge sources exploit 881's rich representation of domain and control knowledge, actions.

We present a new approach to deductive design synthesis, the Residue Approach, in which designs are represented as sets of constraints. Previous approaches, such as PROLOG [181 or the work of Manna and WaWinger [111, express designs as bindings on single terms. We give a complete and sound procedure for Ending sets of propositions constituting a legal design. The size of the search space of the procedure and the advantages and disadvantages of the Residue Approach are analysed. In particular we show how Residue can avoid backtracking caused by making design decisions of overly coarse granularity. In contrast, it is awkward for the single term approaches to do the same. In addition we give a rule for constraint propagation in deductive synthesis, and show its use in pruning the design space. Finally, Residue is related to other work, in particular, to Default Logic [16] and to Assumption-Based Truth Maintenance [1].

Thi3 framework generalizes previous work on cooperation without communication, and shows the ability of communication to resolve conflicts among agents having disparate goals. Using a deal-making mechanism, agents are able to coordinate and cooperate more easily than in the communication-free model. In addition, there are certain types of interactions where communication makes possible mutually beneficial activity that is otherwise impossible to:oordinate.

Counterfactuals are a form of commonsense non-monotonic inference that has been of long-term interest to philosophers.

Arguments are presented in favor of the answer "yes". The intuitive appeal (or lack thereof) of probabilities is considered briefly. The theoretical adequacies of probabilistic methods are investigated by considering them in light of McCarthy's "typology of uses of non-monotonic reasoning." A quantitative approach which overcomes the usual need for a priori probabilities is presented. Some of the practical advantages of using probabilities in a production system are described.