Online research in philosophy

Made-Up Minds addresses fundamental questions of learning and concept invention by means of an innovative computer program that is based on the cognitive ...

Recently, there has been a resurgence of interest in general, comprehensive models of human cognition. Such models aim to explain higher-order cognitive faculties, such as deliberation and planning. Given a computational representation, the validity of these models can be tested in computer simulations such as software agents or embodied robots. The push to implement computational models of this kind has created the field of artificial general intelligence (AGI). Moral decision making is arguably one of the most challenging tasks for computational approaches to higher-order cognition. The need for increasingly autonomous artificial agents to factor moral considerations into their choices and actions has given rise to another new field of inquiry variously known as Machine Morality, Machine Ethics, Roboethics, or Friendly AI. In this study, we discuss how LIDA, an AGI model of human cognition, can be adapted to model both affective and rational features of moral decision making. Using the LIDA model, we will demonstrate how moral decisions can be made in many domains using the same mechanisms that enable general decision making. Comprehensive models of human cognition typically aim for compatibility with recent research in the cognitive and neural sciences. Global workspace theory, proposed by the neuropsychologist Bernard Baars (1988), is a highly regarded model of human cognition that is currently being computationally instantiated in several software implementations. LIDA (Franklin, Baars, Ramamurthy, & Ventura, 2005) is one such computational implementation. LIDA is both a set of computational tools and an underlying model of human cognition, which provides mechanisms that are capable of explaining how an agent’s selection of its next action arises from bottom-up collection of sensory data and top-down processes for making sense of its current situation. We will describe how the LIDA model helps integrate emotions into the human decision-making process, and we will elucidate a process whereby an agent can work through an ethical problem to reach a solution that takes account of ethically relevant factors.

This interdisciplinary book presents recent work on emotions in neuroscience, cognitive science, philosophy, computer science, artificial intelligence, and...

The perspective of modeling knowledge in Artificial Intelligence is that these models are equal to the knowledge itself (e.g. equate the map with the territory). This encoding view treats knowledge as if it were primarily verbal and assumes that verbal concepts themselves can be replaced by descriptions of concepts—as if a body of descriptions and neural categorizations were equivalent mechanisms for generating behavior.[ ] This paper describes a number of concepts around the notion of ‘situatedness’: situated cognition, situated action, situated learning, and the concept of autopoiesis as an organizing principle. Situatedness changes the way we think about how knowledge is created (learning) and applied (action). In this light knowledge management changes its meaning from managing the knowledge of an organization to managing the situation in which learning happens. Collaboration and participation become the key management principles. In this paper we propose that Brahms (Business Re-design Agent-based Holistic Modeling System), an activity-based multi-agent modeling environment, allows us to model knowledge in situated actions and learning in human activities.

This paper analyzes epistemological and ontological dimensions of Human-Computer Interaction (HCI) through an analysis of the functions of computer systems in relation to their users. It is argued that the primary relation between humans and computer systems has historically been epistemic: computers are used as information-processing and problem-solving tools that extend human cognition, thereby creating hybrid cognitive systems consisting of a human processor and an artificial processor that process information in tandem. In this role, computer systems extend human cognition. Next, it is argued that in recent years, the epistemic relation between humans and computers has been supplemented by an ontic relation. Current computer systems are able to simulate virtual and social environments that extend the interactive possibilities found in the physical environment. This type of relationship is primarily ontic, and extends to objects and places that have a virtual ontology. Increasingly, computers are not just information devices, but portals to worlds that we inhabit. The aforementioned epistemic and ontic relationships are unique to information technology and distinguish human-computer relationships from other human-technology relationships.