In Between Facts and Norms, Jürgen Habermas works out the legal and political implications of his Theory of Communicative Action (1981), bringing to fruition the project announced with his publication of The Structural Transformation of the Public Sphere in 1962. This new work is a major contribution to recent debates on the rule of law and the possibilities of democracy in postindustrial societies, but it is much more. The introduction by William Rehg succinctly captures the special nature of the work, (...) noting that it offers a sweeping, sociologically informed conceptualization of law and basic rights, a normative account of the rule of law and the constitutional state, an attempt to bridge normative and empirical approaches to democracy, and an account of the social context required for democracy. Finally, the work frames and caps these arguments with a bold proposal for a new paradigm of law that goes beyond the dichotomies that have afflicted modern political theory from its inception and that still underlie current controversies between so-called liberals and civic republicans. The book includes a postscript written in 1994, which restates the argument in light of its initial reception, and two appendixes, which cover key developments that preceded the book. Habermas himself was actively involved in the translation, adapting the text as necessary to make it more accessible to English-speaking readers. (shrink)

In their introduction to this volume, Ram and Leake usefully distinguish between task goals and learning goals. Task goals are desired results or states in an external world, while learning goals are desired mental states that a learner seeks to acquire as part of the accomplishment of task goals. We agree with the fundamental claim that learning is an active and strategic process that takes place in the context of tasks and goals (see also Holland, Holyoak, Nisbett, and Thagard, 1986). (...) But there are important questions about the nature of goals that have rarely been addressed. First, how can a cognitive system deal with incompatible task goals? Someone may want both to get lots of research done and to relax and have fun with his or her friends. Learning how to accomplish both these tasks will take place in the context of goals that cannot be fully realized together. Second, how are goals chosen in the first place and why are some goals judged to be more important than others? People do not simply come equipped with goals and priorities: we sometimes have to learn what is important to us by adjusting the importance of goals in the context of other compatible and incompatible goals. This paper presents a theory and a computational model of how goals can be adopted or rejected in the context of decision making. In contrast to classical decision theory, it views decision making as a process not only of choosing actions but also of evaluating goals. Our theory can therefore be construed as concerned with the goal-directed learning of goals. (shrink)

Choosing the right plan is often choosing the more coherent plan: but what is coherence? We argue that coherence-directed practical inference ought to be represented computationally. To that end, we advance a theory of deliberative coherence, and describe its implementation in a program modelled on Thagard's ECHO. We explain how the theory can be tested and extended, and consider its bearing on instrumentalist accounts of practical rationality.

This paper provides a computational characterization of coherence that applies to a wide range of philosophical problems and psychological phenomena. Maximizing coherence is a matter of maximizing satisfaction of a set of positive and negative constraints. After comparing five algorithms for maximizing coherence, we show how our characterization of coherence overcomes traditional philosophical objections about circularity and truth.