When developing cognitive agents capable of interacting with humans, it is often challenging to provide a suitable environment in which agent and user are really co-situated. This paper presents a straightforward approach to use Second Life as a persistent, "near natural", and socially rich environment for research on autonomous agents in complex surroundings, learning social skills, and how they are perceived by humans. We describe an integration of our conversational agent Max, and his underlying cognitive architecture, with the Second Life environment. As a result, Max is able to autonomously navigate and multimodally communicate with other avatars inside the Second Life world. Observations from a first trial and reactions of human residents to the virtual agent are presented.
Abstract. Have you ever found yourself in front of a computer and asking it aloud: "Why?" We have constructed a cognitively motivated episodic memory system that enables a virtual guide to respond to this question. The guide, a virtual agent based on a belief-desire-intention (BDI) architecture, is employed in a Virtual Reality (VR) scenario where he accompanies a human visitor on a tour through a city. In this paper we explain how the agents memorizes events and episodes according to an event-indexing model and how the interaction is enhanced by using these memories. We argue that due to the cognitively motivated nature of the event-indexing model every interaction situation can be described, memorized, recalled and explained by the agent.
Abstract:In this paper we introduce a metric to compare events and episodes in the episodic memory system of a virtual agent. The agent, a virtual tour guide based on a belief -desire -intention cognitive architecture, uses his memories to improve the walks around a virtual city. The guide's past experiences are memorized as events and organized into episodes. Each event is indexed along six dimensions and is comparable on each dimension with a distinct distance function. This is then utilized to measure the similarity between episodes.
Abstract:This paper describes how the guiding capabilities of a virtual agent with a belief -desire -intention cognitive architecture can be enhanced by adding an episodic memory. We describe how the theories of episodic memory and event segmentation can be applied to the architecture of our virtual agent Max, and how to create an index according to the event indexing model. Having memories of past experiences will enable our agent to have improved plans how to react in future interaction.
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