During his long and continuing scholarly career, Patrick Suppes has contributed significantly both to the sciences and to scientific philosophies. In this volume, an international group of Suppes’s colleagues, collaborators, and students seeks to build upon Suppes’s insights. Each of their essays is accompanied by a response from Suppes himself, which together create a uniquely engaging dialogue. Suppes and his peers explore a diverse array of topics including the relationship between science and philosophy; the philosophy of physics; problems in the foundations of mathematics; theory of measurement, decision theory, and probability; the foundations of economics and political theory; psychology, language, and the philosophy of language; Suppes’s most recent research in neurobiology; and the alignment (or misalignment) of method and policy.

Robot technology will find wide-scale use only when a robotic device can be given commands and taught new tasks in a natural language. How could a robot understand instructions expressed in English? How could a robot learn from instructions? Crangle and Suppes begin to answer these questions through a theoretical approach to language and learning for robots and by experimental work with robots.

The authors develop the notion of an instructable robot—one which derives its intelligence in part from interaction with humans. Since verbal interaction with a robot requires a natural language semantics, the authors propose a natural-model semantics which they then apply to the interpretation of robot commands. Two experimental projects are described which provide natural-language interfaces to robotic aids for the physically disabled. The authors discuss the specific challenges posed by the interpretation of "stop" commands and the interpretation of spatial prepositions.

The authors also examine the use of explicit verbal instruction to teach a robot new procedures, propose ways a robot can learn from corrective commands containing qualitative spatial expressions, and discuss the machine-learning of a natural language use to instruct a robot in the performance of simple physical tasks. Two chapters focus on probabilistic techniques in learning.