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An alternative is to compile the logical specification of an agent into a form more amenable to efficient decision making The difference is rather like the distinction between interpreted and compiled programming languages The best-known example of this work is the situated automata paradigm of Rosenschein and Kaelbling (1996) A review of the role of logic in intelligent agents may be found in Wooldridge (1997) Finally, for a detailed discussion of calculative rationality and the way that it has affected thinking in A (see Russell and Subramanian, 1 1995) The main references to Agent0 are Shoham (1990, 1993) Shoham's AOP proposal has been enormously influential in the multiagent systems community In addition to the reasons set out in the main text, there are other reasons for believing that an intentional stance will be useful for understanding and reasoning about computer programs (Huhns and Singh, 1998).

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FIGURE 3-9

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First, and perhaps most importantly, the ability of heterogeneous, self-interested agents to communicate seems to imply the ability to talk about the beliefs, aspirations, and intentions of individual agents For example, in order to coordinate their activities, agents must have information about the intentions of others (Jennings, 1993a)This idea is closely related to Newell's knowledge level (Newell, 1982) Later in this book, we will see how mental states such as beliefs, desires, and the like are used to give a semantics to speech acts (Searle, 1969; Cohen and Levesque, 1990a) Second, mentalistic models are a good candidate for representing information about end users For example, imagine a tutoring system that works with students to teach them Java programming One way to build such a system is to give it a model of the user Beliefs, desires, intentions, and the like seem appropriate for the make-up of such models.

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Figure 20.1 During any severe market decline, a critical policy issue is whether the government will intervene and how. These charts illustrate the expected outcome of any attempt by the government to support corporate bonds, in three phases. Phase 1: Corporate bond crisis. Because of spreading failures and defaults, investors lose confidence in the ability of companies to pay the interest and principal on corporate bonds. So they sell their bonds, driving the bond prices lower (and interest rates higher). However, since investors continue to trust the government, the crisis has less negative impact on government bond prices. As corporate bond prices fall, the spread or difference between corporate and government bonds broadens sharply. Phase 2: Government rescues corporate bonds. The government buys corporate bonds with funds that it has raised from government bond investors. This boosts the perceived and actual value of corporate bonds. But, at the same time, it lowers the value of government bonds, prompting investors to sell their government bond holdings. Corporate bond prices go up but government prices fall. As a result, the spread between them narrows. Phase 3: Government rescue is abandoned. To prevent a collapse in its government bonds, the government is forced to abandon its rescue of corporate bonds and accept the consequences of a collapsing corporate bond market. If the government sought to purchase common stocks instead of corporate bonds, the sequence of events described here would be very similar.

Michael Fisher's Concurrent MetateM language is described in Fisher (1994); the execution algorithm that underpins it is described in Barringer et a[(1989)Since Shoham's proposal, a number of languages have been proposed wbch claim to be agent oriented Examples include Becky Thomas's Planning Communicating.

FIGURE 35.8 A data file is created in Microsoft Excel (top) with three data records. Each row is a separate record and the cells across each row horizontally represent the field data for the respective record. Row 1 contains the field names that match the PDF form (bottom).