Symbol Grounding

From InterSciWiki

Brian Skyrms, 1999. Chapter on "The Evolution of Meaning" (Evolutionary Game Theory), in, "Evolution of the Social Contract http://books.google.com/books?id=dSxGOOn3pw4C&pg=PP1&ots=e-oocAAtLi&dq=inauthor:Brian+inauthor:Skyrms&sig=iscLeTI3FwZ7YdvRZyTXQz 4Rq-w

Nils Ferrand, Tam-Kien Duong, 2007. Modeling knowledge societies

Luc Steels, 2007. The Symbol Grounding Problem has been solved. So what's next? http://www.citeulike.org/user/majak/article/1052625 Steels addresses as the symbol grounding problem as "the question originally posed by Searle: Can a robot deal with grounded symbols? More precisely, is it possible to build an artificial system that has a body, sensors and actuators, signal and image processing and pattern recognition processes, and information structures to store and use semiotic maps, and uses all that, for example in communication about the real world." His solution lies with the formulation of rule governed domains in the form of Wittgenstein language games. The problem may not have been solved, however, if the problem of reflexivity is posed: if a robot's learning through use (interaction with others) how can the problem of "hijacking" be solved where the robot is deliberately taught misleading expressions? Some forms of causal reasoning about context and intent of other speakers might be required.

Here is the solution proposed (p. 5-6): "So the key question for symbol grounding is actually another question, well formulated by Harnad [7]: If someone claims that a robot can deal with grounded symbols we expect that this robot autonomously establishes the semiotic map that it is going to use to relate symbols with the world.

Semiotic Dynamics.

Very recent developments in AI have now shown that this second question can also be resolved. We now know how to conceive of artificial systems that autonomously set up and coordinate semiotic landscapes and there is a growing number of concrete realisations achieving this [11]. That is why I believe we can now say that the symbol grounding problem is solved. The breakthrough idea is to set up a particular kind of ’semiotic’ dynamics. Each agent is endowed with the capacity to invent new concepts which initially act like hooks. The concepts get progressively more meaning by associating methods with them that relate the concepts to the world or by associating symbols with them to coordinate their use within the group. Agents interact with each other, for example through language games, and as part of the interaction they adapt both their grounding methods and the relation to symbols. One way to implement this adaptation is to have weighted links that get updated and changed based on success in interactions. If all this is done right, we see a gradual convergence towards shared semiotic systems among the agents, in the sense that their concepts become sufficiently coordinated to make successful communication possible."

This might not be enough to solve the problem. Other approaches to symbol grounding and interpretation are given in both artificial intelligence and econometric approaches to causality, which avoid the dilemmas of Steels' model for artificial intelligence through arbitrary symbolic communication in the context of Wittgensteinain games. These approaches go beyond autonomy to establish what might be called criteria for validation and reliability in symbol grounding constructs.