Plato

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Background Ideas

Charles Peirce's triadic semiotic relation attempted to show the atomic relation between objects (x), their phenomenal experience as signs (S), and their dispositional affect (z) on a mind.


Peirce's triadic relation arose from introspective investigations into the nature of mind. However, when an operational explanation is sought, the Cartesian limitations of the triad becomes apparent after the different ontologic system levels are taken into account - see Whobrey (2001).

Last updated: 23rd September 2008.

Mild Artificial Intelligence Website
Explorations into machines with minds


Objective

A goal of this research is to instill machines, such as robots, with useful mental properties so that they may operate more effectively in social and hostile environments.

Current Projects

Current research is focused on the production of a practical modelling methodology for developing decision systems with simple minds, i.e. cognitive engineering, such as robot control systems. This is embodied in the Plato project that aims to provide a development environment for constructing decision systems with minds.

Overview of Mild AI

John Searle (1984) has characterised the domain of artificial intelligence (AI) by distinguishing between weak AI, according to which computers are useful tools for studying mind, and strong AI, according to which an equivalence is made between mind and programs, such that computers executing programs actually possess mind. Between this dychotomy there is a third alternative, namely: the prospects and promise of mild AI, according to which a suitable computer is capable of possessing species of mentality that may differ from and be weaker than ordinary human mentality, but qualify as "mentality" nonetheless.

The Need for "New Stuff"

The difficulty of creating a system that is inherently intelligent has existed since the field of artificial intelligence was first formed. This is a complex problem that is difficult to solve using contemporary programming formalisms. Rodney Brooks (2001), head of MIT's AI Laboratory, has suggested that this is because it may require some new stuff.
To address Brooks' problem, one approach might be to devise systems that are inherently intelligent. For example, it is desirable to be able to develop an intelligent system that doesn't have to be completely programmed explicitly. One way of achieving this might be by instilling systems with minds, since we know some kinds of minds have intelligent abilities.
James Fetzer (1998) has suggested that the conception of mind as a causal system based on a dispositional interpretation of Charles Peirce's semiotics is philosophically coherent at a phenomenal level. Hence, the new stuff may involve instilling machines with a species of machine mentality based on the causal system approach.
Consequently, Darren Whobrey (1999) and later research, investigated the requirements that machines with minds would need to satisfy. Prototypes of artificial minds based on this research are now being implemented under the Plato project. For details on some of the earlier research results, see the articles and reports here.

Keywords

Mild artificial intelligence, causal systems, consciousness, dispositions, interpretation, minds, qualia, representation, semiotics, signification, mind-body problem, interpreter regress problem, binding problem.