The emergence of language among autonomous agents

Suppose some autonomous shopbot agents had been representing us by dealing with a vendor's pricebot, and suppose they didn't share an agent communication language (ACL). What should they know at a fundamental level, what could each point to, and how could they establish a common language? Recent research at the University of Texas at Arlington has shown that agents first establish a common vocabulary, progress to a primitive language similar to human pidgin, then enrich the language's grammar to develop a creole, and eventually arrive at a full-blown ACL. During this process, the vocabulary and grammatical structures most important to the agents' task at hand appear first. Thus, shopbots and pricebots will first learn to communicate about various types of goods and money, while softbots that deal with, say, stock market investing will likely develop a different language. However, we must make some assumptions about the agents. First, the agents must be knowledge based. Second, the agents must be purposeful, with well-defined goals, that is, precise descriptions of the states of the world they are to bring about. Third, the agents must be rational. This means they act so as to further their goals, given what they know.