Interactivist Summer Institute

July 23 - 27, 2001

Lehigh University


Mark H. Bickhard: Interactivism: From Metaphysics to Rational Agents

Robert Campbell, John Christopher: Social and Ethical Beings

Cliff Hooker, Mark H. Bickhard: Interactivism, Neuroethology and the Explanation of Behavior

Georgi Stojanov , Goran Trajkovski: Interactivism in AI


Interactivism: From Metaphysics to Rational Agents

Mark H. Bickhard


Interactivism began as a solution to the skeptical problem in epistemology. That solution, however, involved deep presuppositions that were in conflict with the dominant metaphysics of contemporary studies of the mind and the person, from philosophy to psychology to artificial intelligence and robotics. Uncovering those presuppositions and conflicts, and developing alternative models that are consistent with the presuppositions of interactivism has created a systemic theory and philosophy that begins in metaphysics, and spans from biology through studies of the mind and person, including the emergence of social realities and social beings. This tutorial will present a surview of the history and scope of interactivism, with special focus on selected topics, such as representation, development, consciousness, language, and rationality.


Social and Ethical Beings

Robert Campbell

John Christopher


Interactivism offers a different conception of human selves and human social relations and lends support to a distinctive moral psychology. We will present an interactivist conception of the self and its development, and develop a basic distinction between goals, values, and metavalues. We will show how this conception avoids splitting moral values off from nonmoral values, or moral reasoning from moral personality, and allows for personal morality as well as social morality. We will also address cross-cultural differences in moral psychology.


Interactivism, Neuroethology and the Explanation of Behavior

Cliff Hooker

Mark H. Bickhard


Classical neuroscience research into perception tends to presuppose an upstream correspondence model of representation, but this sits uneasily with an increasingly clear recognition that cognitive systems have evolved because of the way they make a difference to behavior. This tutorial will examine research programs in neuroscience that are adopting a more overtly interactivist orientation, particularly in neuroethology and research on the early evolution of nervous systems. Along the way it will critically examine the complex ways that the term 'representation' is used in cognitive neuroscience. 


Interactivism in AI

Georgi Stojanov

Goran Trajkovski


This tutorial will give an overview of the treatment and construal of representation within AI and intelligent robotics in the last 50 years. This is not as difficult a task as it might seem. Beginning with the classical AI projects (LT, GSP, The Whirling Dervish, SHRDLU, Shakey, etc.) we'll reveal the hidden assumptions regarding the nature of intelligence and intelligent behavior, and their implications for the projects discussed. We will comment on how a given construal of representation has favored particular views about perception, learning, and language. The stress will be put on the last 10 years in these fields. The beginning of this period was a time when it began to be acknowledged that classical approaches and the alternatives that followed (connectionism, behavior based architectures) hadn't met expectations. This was also a period of radical re-examination of the roots of these disciplines. We will review some of the projects within this period (works of Drescher, Mataric, Tani, Hofstadter, etc.). Inspired by Piaget's genetic epistemology, Gibson's theory of perception, by the new findings in animal learning, it can be said that these projects introduced a new interactivist spirit into the field. Concluding the tutorial, we will discuss these new architectures for intelligence within Bickhard's interactivist framework, the convergence of ideas coming from diferent fields (e.g. recent works of O'Regan and Noa on visual perception), and will give short term predictions for the development of AI and cognitive robotics.



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