New computer systems of discovery create a research program for logic and philosophy of science. These systems consist of inference rules and control knowledge that guide the discovery process. Their paths of discovery are influenced by the available data and the discovery steps coincide with the justification of results. The discovery process can be described in terms of fundamental concepts of artificial intelligence such as heuristic search, and can also be interpreted in terms of logic. The traditional distinction that places (...) studies of scientific discovery outside the philosophy of science, in psychology, sociology, or history, is no longer valid in view of the existence of computer systems of discovery. It becomes both reasonable and attractive to study the schemes of discovery in the same way as the criteria of justification were studied: empirically as facts, and logically as norms. (shrink)

Clark Glymour defined bootstrap-confirmation as a three-place relation: “Evidence E bootstrap confirms hypothesis H with respect to theory T.“ By an ingenious choice of examples, David Christensen has shown that Glymour's definition is satisfied in a class of cases in which confirmation seems to be highly counterintuitive. Responding to Christensen's criticism, Glymour revised his 1980 definition of bootstrap confirmation, by introducing an additional condition that rules out Christensen's counterexamples.

Machine discovery is a new area of artificial intelligence, dealing with computer systems which make discoveries. An automated discovery system can be imagined similarly to a human discoverer or to the sommunity of scientists-discoverers, as a robot that makes experiments and uses empirical data to develop theories. The author argues that construction of discovery system and theories of their functioning is a new and attractive program for the philosophy of science. He reviews the existing discovery systems and presents the theoretical (...) schema emerging from their analysis. A large reference list provides directions for further studies. (shrink)

Our consciousness is a challenge both for the scientific and the computer reductionism. In the article I show that in everything which appears in our awareness there is an element which cannot be captured by scientific experience and computer models. Because our minds interact with the material world, only interactionism is compatible with our whole experience. But there is no sense to demand that the mechanism of this interaction should be given, because such mechanism cannot exist. Subsequently I reject evolutionary (...) arguments for materialist monism. At the end of the article I point that interactionism does not exclude the posiibility of progress in modeling scientifically external observational aspects of consciousness. (shrink)

Construction of a robot discoverer can be treated as the ultimate success of automated discovery. In order to build such an agent we must understand algorithmic details of the discovery processes and the representation of scientific knowledge needed to support the automation. To understand the discovery process we must build automated systems. This paper investigates the anatomy of a robot-discoverer, examining various components developed and refined to a various degree over two decades. We also clarify the notion of autonomy of (...) an artificial agent, and we discuss the ways in which machine discoverers become more autonomous. Finally we summarize the main principles useful in construction of automated discoverers and we discuss various possible limitations of automation. (shrink)