A "Consciousness"-Based Architecture for a Functioning Mind

Here we describe an architecture designed to accommodatemultiple aspects of human mental functioning. In a roughly star-shaped configuration centered on a “consciousness” module, the architecture accommodates perception, associative memory, emotions, action-selection, deliberation, language generation, behavioral and perceptual learning, self-preservation and metacognition modules. The various modules (partially) implement several different theories of these various aspects of cognition. The mechanisms used in implementing the several modules have been inspired by a number of different “new AI” techniques. One software agent embodying much of the architecture is in the debugging stage (Bogner et al. in press). A second, intending to include all of the modules of the architecture is well along in the design stage (Franklin et al. 1998). The architecture, together with the underlying mechanisms, comprises a fairly comprehensive model of cognition (Franklin & Graesser 1999). The most significant gap is the lack of such human-like senses as vision and hearing, and the lack of realworld physical motor output. The agents interact with their environments mostly through email in natural language. The “consciousness” module is based on global workspace theory (Baars 1988, 1997). The central role of this module is due to its ability to select relevant resources with which to deal with incoming perceptions and with current internal states. Its underlying mechanism was inspired by pandemonium theory (Jackson 1987). The perception module employs analysis of surface features for natural language understanding (Allen 1995). It partially implements perceptual symbol system theory (Barsalou 1999), while its underlying mechanism constitutes a portion of the copycat architecture (Hofstadter & Mitchell 1994). Within this architecture the emotions play something of the role of the temperature in the copycat architecture and of the gain control in pandemonium theory. They give quick indication of how well things are going, and influence both actionselection and memory. The theory behind this module was influenced by several sources (Picard 1997, Johnson 1999, Rolls 1999). The implementation is via pandemonium theory enhanced with an activation-passing network. The action-selection mechanism of this architecture is implemented by a major enhancement of the behavior net (Maes 1989). Behavior in this model corresponding to goal contexts in global workspace theory. The net is fed at one end by environmental and/or internal state influences, and at the other by fundamental drives. Activation passes in both directions. The behaviors compete for execution, that is, to become the dominant goal context. The deliberation and language generation modules are implemented via pandemonium theory. The construction of scenarios and of outgoing messages are both accomplished by repeated appeal to the “consciousness” mechanism. Relevant events for the scenarios and paragraphs for the messages offer themselves in response to “conscious” broadcasts. The learning modules employ case-based reasoning (Kolodner 1993) using information gleaned from human correspondents. Metacognition is based on fuzzy classifier systems (Valenzuela-Rendon 1991). As in the copycat architecture, almost all of the actions taken by the agents, both internal and external, are performed by codelets. These are small pieces of code typically doing one small job with little communication between them. Our architecture can be thought of as a multi-agent system overlaid with a few, more abstract mechanisms. Altogether, it offers one possible architecture for a relatively fully functioning mind. One could consider these agents as early attempts at the exploration of design space and niche space (Sloman 1998).