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Drew McDermott

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

20 papers
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Possible papers

20

JAAMAS Journal 2026 Journal Article

Derivation of Glue Code for Agent Interoperation

  • Mark Burstein
  • Drew McDermott
  • STEPHEN J. WESTFOLD

Abstract Getting agents to communicate requires translating the data structures of the sender (the source representation) to the format required by the receiver (the target representation). Assuming that there is a formal theory of the semantics of the two formats, which explains both their meanings in terms of a neutral topic domain, we can cast the translation problem as solving higher-order functional equations. Some simple rules and strategies apparently suffice to solve these equations automatically. The strategies may be summarized as: decompose complex expressions, replacing topic-domain expressions with source-domain expressions when necessary. A crucial issue is getting the required formal theories of the source and target domains. We believe it is sufficient to find partial formalizations that grow as necessary.

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AIJ Journal 2007 Journal Article

Level-headed

  • Drew McDermott

I don't believe that human-level intelligence is a well defined goal. As the cognitive-science community learns more about thinking and computation, the mileposts will keep changing in ways that we can't predict, as will the esteem we assign to past accomplishments. It would be fun to have a computer that could solve brain teasers as well as the average scientist, but focusing on such things, besides being parochial, overlooks the crucial role language plays in everything humans do, a role we understand hardly at all on a computational level. I am optimistic that we will eventually figure language out, but not without new ideas. Plus, when we can talk to machines, will we understand each other?

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AIJ Journal 1999 Journal Article

Using regression-match graphs to control search in planning

  • Drew McDermott

Classical planning is the problem of finding a sequence of actions to achieve a goal given an exact characterization of a domain. An algorithm to solve this problem is presented, which searches a space of plan prefixes, trying to extend one of them to a complete sequence of actions. It is guided by a heuristic estimator based on regression-match graphs, which attempt to characterize the entire subgoal structure of the remaining part of the problem. These graphs simplify the structure by neglecting goal interactions and by assuming that variables in goal conjunctions should be bound in such a way as to make as many conjuncts as possible true without further work. In some domains, these approximations work very well, and experiments show that many classical planning problems can be solved with very little search.

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AIJ Journal 1994 Journal Article

Modeling a dynamic and uncertain world I

  • Steve Hanks
  • Drew McDermott

Intelligent agency requires some ability to predict the future. An agent must ask itself what is presently its best course of action given what it now knows about what the world will be like when it intends to act. This paper presents a system that uses a probabilistic model to reason about the effects of an agent's proposed actions on a dynamic and uncertain world, computing the probability that relevant propositions will hold at a specified point in time. The model allows for incomplete information about the world, the occurrence of exogenous (unplanned) events, unreliable sensors, and the possibility of an imperfect causal theory. The system provides an application program with answers to questions of the form “is the probability that ϕ will hold in the world at time t greater than τ? ” It is unique among algorithms for probabilistic temporal reasoning in that it tries to limit its inference according to the proposition, time, and probability threshold provided by the application. The system will also notify the application if subsequent evidence invalidates its answer to a query.

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AIJ Journal 1991 Journal Article

A general framework for reason maintenance

  • Drew McDermott

There are several different kinds of reason-maintenance system in existence, which provide rather different functionalities. I present a general structure that subsumes most such systems, and that allows some new behaviors to emerge. The general framework is based on logic-style clauses (disjunctions of literals) instead of justifications. Literals are tagged with labels that say what assumption sets make them true and false. Nonmonotonicity is implemented by allowing clauses to contain disjuncts of the form Lp, which supports propagation through a clause whenever p is not known to be true. The resulting system supports two popular styles of dependency-directed backtracking, using nogoods and assumption retraction. Assumption retraction does not require a separate contradiction-elimination phase, but occurs automatically during label propagation. Label propagation can be achieved by the usual variants of Boolean constraint propagation, provided there are no “odd loops” through the clauses, and it can be shown that the system itself never creates odd loops.

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AIJ Journal 1988 Journal Article

Problems in formal temporal reasoning

  • Yoav Shoham
  • Drew McDermott

Ever since its introduction by McCarthy and Hayes in 1969, the so-called frame problem has been the object of much fascination and debate. Although it was defined in the narrow context of the situation calculus, a specific temporal formalism, it was clear from the start that it is in fact a manifestation of some fundamental problem in temporal reasoning. Our aim in this informal paper is to identify the general form of certain classes of problems that arise in formal temporal reasoning. We argue that problems such as the frame problem arise from the conflicting desires to reason both rigorously and efficiently about the future. This conflict does not depend on the particular underlying temporal formalism. In particular, we identify two formalism-independent problems, called the qualification problem and the extended prediction problem, which subsume the frame problem. To illustrate the fact that these problems are indeed inherent to the prediction task and not to a particular formalism, we show that they arise in two distinct frameworks: classical mechanics, and Hayes' histories notation.

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AIJ Journal 1987 Journal Article

Nonmonotonic logic and temporal projection

  • Steve Hanks
  • Drew McDermott

Nonmonotonic formal systems have been proposed as an extension to classical first-order logic that will capture the process of human “default reasoning” or “plausible inference” through their inference mechanisms, just as modus ponens provides a model for deductive reasoning. But although the technical properties of these logics have been studied in detail and many examples of human default reasoning have been identified, for the most part these logics have not actually been applied to practical problems to see whether they produce the expected results. We provide axioms for a simple problem in temporal reasoning which has long been identified as a case of default reasoning, thus presumably amenable to representation in nonmonotonic logic. Upon examining the resulting nonmonotonic theories, however, we find that the inferences permitted by the logics are not those we had intended when we wrote the axioms, and in fact are much weaker. This problem is shown to be independent of the logic used; nor does it depend on any particular temporal representation. Upon analyzing the failure we find that the nonmonotonic logics we considered are inherently incapable of representing this kind of default reasoning. The first part of the paper is an expanded version of one that appeared in the 1986 AAAI proceedings. The second part reports on several responses to our result that have appeared since the original paper was published.

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AIJ Journal 1984 Journal Article

Planning routes through uncertain territory

  • Drew McDermott
  • Ernest Davis

Planning routes and executing them requires both topological and metric information. A natural implementation of a ‘cognitive map’ might therefore consist of an assertional data base for topological information and a ‘fuzzy map’ for the metric information. A fuzzy map captures facts about objects by recording their relative positions, orientations, and scales in convenient frames of reference. It is fuzzy in the sense that coordinates are specified to lie in a range rather than having fixed values. The fuzzy map allows easy retrieval of information. The same information is also represented in a discrimination tree, which allows an object to be retrieved given its location and other attributes. The problem of constructing a fuzzy map is more difficult; we present a partial solution, an algorithm that assimilates a fact first by imposing constraints on the fuzzy coordinates of the objects involved, then by rearranging or growing the tree of frames of reference. Route planning is modelled as a process of finding the overall direction and topology of the path, then filling in the details by deciding how to go around barriers. It uses the retrieval algorithms. Our program SPAM carries out all these processes.

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AAAI Conference 1983 Conference Paper

Data Dependencies on Inequalities

  • Drew McDermott

Numerical inequalities present new challenges to data-base systems that keep track of "dependencies," or reasons for beliefs. Care must be taken in interpreting an inequality as an assertion, since occasionally a "strong" interpretation is needed, that the inequality is best known bound on a quantity. Such inequalities often have many proofs, so that the proper response to their erasure is often to look for an alternative proof. Fortunately, abstraction techniques developed by data-dependency theorists are robust enough that they can be extended fairly easily to handle these problems. The key abstractions involved are the "ddnode," an abstract assertion as seen by the data-dependency system, and its associated "signal function," which performs indexing, re-deduction, and garbage-collection functions. Such signal functions must have priorities, so that they don’t clobber each other when they run.

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AAAI Conference 1982 Conference Paper

ARBY: Diagnosis with Shallow Causal Models

  • Drew McDermott

Arby is a software system or higher order language for writing expert systems to do diagnosis in electronic systems. As such, it is similar to EMYCIN (Van Melle 1982) in application, but quite different in design. It is rule-based to an extent, but the rules are written in predicate calculus. It resembles Caduceus (Pople 1977) in its mechanisms for refining and combining hypotheses.

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AIJ Journal 1980 Journal Article

Non-monotonic logic I

  • Drew McDermott
  • Jon Doyle

‘Non-monotonic’ logical systems are logics in which the introduction of new axioms can invalidate old theorems. Such logics are very important in modeling the beliefs of active processes which, acting in the presence of incomplete information, must make and subsequently revise assumptions in light of new observations. We present the motivation and history of such logics. We develop model and proof theories, a proof procedure, and applications for one non-monotonic logic. In particular, we prove the completeness of the non-monotonic predicate calculus and the decidability of the non-monotonic sentential calculus. We also discuss characteristic properties of this logic and its relationship to stronger logics, logics of incomplete information, and truth maintenance systems.

Details DOI
v2026.09.13