<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml">Orseau and Ring, as well as Dewey, have recently described problems, including self-delusion, with the behavior of agents using various definitions of utility functions. An agent's utility function is defined in terms of the agent's history of interactions with its environment. This paper argues, via two examples, that the behavior problems can be avoided by formulating the utility function in two steps: 1) inferring a model of the environment from interactions, and 2) computing utility as a function of the environment model. Basing a utility function on a model that the agent must learn implies that the utility function must initially be expressed in terms of specifications to be matched to structures in the learned model. These specifications constitute prior assumptions about the environment so this approach will not work with arbitrary environments. But the approach should work for agents designed by humans to act in the physical world. The paper also addresses the issue of self-modifying agents and shows that if provided with the possibility to modify their utility functions agents will not choose to do so, under some usual assumptions.</abstract>

Model-based Utility Functions

<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml">Dreyfus' call ‘to make artificial intelligence (AI) more Heideggerian‘ echoes Heidegger's affirmation that pure calculations produce no ‘intelligence’ (Dreyfus, 2007). But what exactly is it that AI needs more than mathematics? The question in the title gives rise to a reexamination of the basic principles of cognition in Husserl's Phenomenology. Using Husserl's Phenomenological Method, a formalization of these principles is presented that provides the principal idea of cognition, and as a consequence, a ‘natural logic’. Only in a second step, mathematics is obtained from this natural logic by abstraction.The limitations of pure reasoning are demonstrated for fundamental considerations (Hilbert's ‘finite Einstellung’) as well as for the task of solving practical problems. Principles will be presented for the design of general intelligent systems, which make use of a natural logic.</abstract>

Is Logic in the Mind or in the World? Why a Philosophical Question can Affect the Understanding of Intelligence

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Journal of Artificial General Intelligence

 Journal of Artificial General Intelligence (JAGI) is a peer-reviewed open-access academic journal, owned by the Artificial General Intelligence Society (AGIS).  Artificial General Intelligence (AGI) is an emerging field aiming at the building of "thinking machines", that is, general-purpose systems with intelligence comparable to that of the human mind. While this was the original goal of Artificial Intelligence (AI), the mainstream of AI research has turned toward domain-dependent and problem-specific solutions; therefore it has become necessary to use a new name to indicate research that still pursues the "Grand AI Dream". Similar labels for this kind of research include "Strong AI", "Human-level AI", etc.  The problems involved in creating general-purpose intelligent systems are very different from those involved in creating special-purpose systems. Therefore, this journal is different from conventional AI journals in its stress on the long-term potential of research towards the ultimate goal of AGI, rather than immediate applications. Articles focused on details of AGI systems are welcome, if they clearly indicate the relation between the special topics considered and intelligence as a whole, by addressing the generality, extensibility, and scalability of the techniques proposed or discussed.  Since AGI research is still in its early stage, the journal strongly encourages novel approaches coming from various theoretical and technical traditions, including (but not limited to) symbolic, connectionist, statistical, evolutionary, robotic and information-theoretic, as well as integrative and hybrid approaches.  Rejection Rate  &gt;30%   Archiving  Sciendo archives the contents of this journal in Portico - digital long-term preservation service of scholarly books, journals and collections.  Plagiarism Policy  The editorial board is participating in a growing community of Similarity Check System's users in order to ensure that the content published is original and trustworthy. Similarity Check is a medium that allows for comprehensive manuscripts screening, aimed to eliminate plagiarism and provide a high standard and quality peer-review process. 

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Volume 3 (2012): Issue 1 (May 2012)

Model-based Utility Functions

Is Logic in the Mind or in the World? Why a Philosophical Question can Affect the Understanding of Intelligence

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