22,430 research outputs found
Learning to Speak and Act in a Fantasy Text Adventure Game
We introduce a large scale crowdsourced text adventure game as a research
platform for studying grounded dialogue. In it, agents can perceive, emote, and
act whilst conducting dialogue with other agents. Models and humans can both
act as characters within the game. We describe the results of training
state-of-the-art generative and retrieval models in this setting. We show that
in addition to using past dialogue, these models are able to effectively use
the state of the underlying world to condition their predictions. In
particular, we show that grounding on the details of the local environment,
including location descriptions, and the objects (and their affordances) and
characters (and their previous actions) present within it allows better
predictions of agent behavior and dialogue. We analyze the ingredients
necessary for successful grounding in this setting, and how each of these
factors relate to agents that can talk and act successfully
Towards Multi-Modal Interactions in Virtual Environments: A Case Study
We present research on visualization and interaction in a realistic model of an existing theatre. This existing ‘Muziek¬centrum’ offers its visitors information about performances by means of a yearly brochure. In addition, it is possible to get information at an information desk in the theatre (during office hours), to get information by phone (by talking to a human or by using IVR). The database of the theater holds the information that is available at the beginning of the ‘theatre season’. Our aim is to make this information more accessible by using multi-modal accessible multi-media web pages. A more general aim is to do research in the area of web-based services, in particu¬lar interactions in virtual environments
Visualizing recommendations to support exploration, transparency and controllability
Research on recommender systems has traditionally focused on the development of algorithms to improve accuracy of recommendations. So far, little research has been done to enable user interaction with such systems as a basis to support exploration and control by end users. In this paper, we present our research on the use of information visualization techniques to interact with recommender systems. We investigated how information visualization can improve user understanding of the typically black-box rationale behind recommendations in order to increase their perceived relevance and meaning and to support exploration and user involvement in the recommendation process. Our study has been performed using TalkExplorer, an interactive visualization tool developed for attendees of academic conferences. The results of user studies performed at two conferences allowed us to obtain interesting insights to enhance user interfaces that integrate recommendation technology. More specifically, effectiveness and probability of item selection both increase when users are able to explore and interrelate multiple entities - i.e. items bookmarked by users, recommendations and tags. Copyright © 2013 ACM
Visualizations for an Explainable Planning Agent
In this paper, we report on the visualization capabilities of an Explainable
AI Planning (XAIP) agent that can support human in the loop decision making.
Imposing transparency and explainability requirements on such agents is
especially important in order to establish trust and common ground with the
end-to-end automated planning system. Visualizing the agent's internal
decision-making processes is a crucial step towards achieving this. This may
include externalizing the "brain" of the agent -- starting from its sensory
inputs, to progressively higher order decisions made by it in order to drive
its planning components. We also show how the planner can bootstrap on the
latest techniques in explainable planning to cast plan visualization as a plan
explanation problem, and thus provide concise model-based visualization of its
plans. We demonstrate these functionalities in the context of the automated
planning components of a smart assistant in an instrumented meeting space.Comment: PREVIOUSLY Mr. Jones -- Towards a Proactive Smart Room Orchestrator
(appeared in AAAI 2017 Fall Symposium on Human-Agent Groups
Towards virtual communities on the Web: Actors and audience
We report about ongoing research in a virtual
reality environment where visitors can interact with
agents that help them to obtain information, to perform
certain transactions and to collaborate with them in order
to get some tasks done. Our environment models a
theatre in our hometown. We discuss attempts to let this
environment evolve into a theatre community where we
do not only have goal-directed visitors, but also visitors
that that are not sure whether they want to buy or just
want information or visitors who just want to look
around. It is shown that we need a multi-user and multiagent
environment to realize our goals. Since our environment
models a theatre it is also interesting to investigate
the roles of performers and audience in this environment.
For that reason we discuss capabilities and personalities of agents. Some notes on the historical development of networked communities are included
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