Given the computational view of cognitive science, it is arguable that all research in artificial intelligence is also research in cognitive science. Nonetheless, certain applications of artificial intelligence techniques to problems in engineering, management, etc., and, perhaps, the development of expert systems do not seem to fall within the scope of cognitive science. Certainly, however, those aspects of artificial intelligence research that might be considered to be ``computational psychology'' or ``computational philosophy'' are also in the domain of cognitive science. Among these are the following: the early work by Newell and Simon on problem solving (the Logic Theorist, the General Problem Solver; cf. Newell, Shaw, & Simon 1963ab), as well as recent work on the SOAR project (Laird, Newell, & Rosenbloom 1987); aspects of knowledge representation that attempt to reflect cognition (e.g., some uses of semantic networks, such as M. Ross Quillian's original theory (1968) and more recent systems such as Stuart C. Shapiro's SNePS (Shapiro 1979; Shapiro & Rapaport 1987), and John R. Anderson's ACT* systems (cf. Anderson 1989); Minsky's theory of frames (cf. Minsky 1981); and Roger Schank's theory of scripts and conceptual dependency (Schank & Abelson 1977)); work on ``naive'' or ``qualitative'' physics, which attempts to develop systems that can reason about physics in ways that humans do on an everyday basis (rather than in ways that professional physicists do) (cf. Hayes 1985); machine learning (cf. Michalski, Carbonell, & Mitchell 1983, 1986); planning; reasoning; natural-language understanding and generation; and computational vision. (For surveys of these and other topics, cf. Shapiro 1987.)