In his application, Stephen Thaler stated that the related work was created autonomously by the "creativity machine" algorithm, and it is a work created by the "work made for hire" doctrine, and that he filed the application by being the proprietor of the machine following the assignment declaration he submitted. On the other hand, Thaler requested reconsideration of this decision stating that it is unconstitutional to require a "human authorship" requirement for registration and that such a requirement is neither included in the law nor the case law. In the subsequent examination, the Office again rejected these requests, reiterating its initial assessments and stating that Thaler did not provide evidence to prove that human-provided sufficient creative contribution to the relevant work or that the human intervention had taken place. Therefore, he argued that the Office's refusal grounds were based on old views that did not address current needs. Evaluating this second request for reconsideration, the Board stated that the law protects the fruits of intellectual labour.

In 1983, I gave the AAAI president's address titled "Artificial Intelligence Prepares for 2001." An article, based on that talk, was published soon after in AI Magazine. In this article, I retract or modify some of the points made in that piece and reaffirm others. Specifically, I now acknowledge the many important facets of AI research beyond high-level reasoning but maintain my view about the importance of integrated AI systems, such as mobile robots. In 1983, I gave the AAAI president's address titled "Artificial Intelligence Prepares for 2001."

A recurring requirement for human-level artificial intelligence is the incorporation of vast amounts of knowledge into a software agent that can use the knowledge in an efficient and organized fashion. This article discusses representations and processes for agents and behavior models that integrate large, diverse knowledge stores, are long-lived, and exhibit high degrees of competence and flexibility while interacting with complex environments. There are many different approaches to building such agents, and understanding the important commonalities and differences between approaches is often difficult. We introduce a new approach to comparing frameworks based on the notions of commitment, reconsideration, and a categorization of representations and processes. We review four agent frameworks, concentrating on the major representations and processes each directly supports.

Deliberation itself can be a computationally costly process and requires This paper shows how belief revision techniques an appropriate intention reconsideration policy which can be used in Defeasible Logic to change rulebased helps the agent to deliberate only when necessary. In this picture, theories characterizing the deliberation process it is still overlooked the problem of changing intentions of cognitive agents. We discuss intention reconsideration not because of the change of beliefs, but because the normative as a strategy to make agents compliant constraints require to do so.

A recurring requirement for human-level artificial intelligence is the incorporation of vast amounts of knowledge into a software agent that can use the knowledge in an efficient and organized fashion. This article discusses representations and processes for agents and behavior models that integrate large, diverse knowledge stores, are long-lived, and exhibit high degrees of competence and flexibility while interacting with complex environments. There are many different approaches to building such agents, and understanding the important commonalities and differences between approaches is often difficult. We introduce a new approach to comparing frameworks based on the notions of commitment, reconsideration, and a categorization of representations and processes. We review four agent frameworks, concentrating on the major representations and processes each directly supports. By organizing the approaches according to a common nomenclature, the analysis highlights points of similarity and difference and suggests directions for integrating and unifying disparate approaches and for incorporating research results from one framework into alternatives.

In 1983, I gave the AAAI president's address titled "Artificial Intelligence Prepares for 2001." An article, based on that talk, was published soon after in "AI Magazine. In this article, I retract or modify some of the points made in that piece and reaffirm others. Specifically, I now acknowledge the many important facets of AI research beyond high-level reasoning but maintain my view about the importance of integrated AI systems, such as mobile robots.

Those of us engaged in artificial intelligence research have the historically unique privilege of asking and answering the most profound scientific and engineering questions that people have ever set for themselves--questions about the nature of those processes that separate us humans from the rest of the universe--namely intelligence, reason, perception, self-awareness, and language. It is clear--to most of us in AI, at least--that our field, perhaps together with molecular genetics, will be society's predominant scientific endeavor for the rest of this century and well into the next...