Hybrid Teams: Flexible Collaboration Between Humans, Robots and Virtual Agents

2016 ◽  
pp. 131-146 ◽  
Author(s):  
Tim Schwartz ◽  
Ingo Zinnikus ◽  
Hans-Ulrich Krieger ◽  
Christian Bürckert ◽  
Joachim Folz ◽  
...  
Keyword(s):  
Virtual Agents ◽  
Hybrid Teams

Hybrid Teams of Humans, Robots, and Virtual Agents in a Production Setting

2016 ◽  
Author(s):  
Tim Schwartz ◽  
Michael Feld ◽  
Christian Burckert ◽  
Svilen Dimitrov ◽  
Joachim Folz ◽  
...  
Keyword(s):  
Virtual Agents ◽  
Hybrid Teams

Agency and rationality: Adopting the intentional stance toward evolved virtual agents.

Decision ◽  
2016 ◽  
Vol 3 (1) ◽  
pp. 40-53 ◽  
Author(s):  
Peter C. Pantelis ◽  
Timothy Gerstner ◽  
Kevin Sanik ◽  
Ari Weinstein ◽  
Steven A. Cholewiak ◽  
...  
Keyword(s):  
Virtual Agents ◽  
Intentional Stance

scholarly journals The Matter of Chance: Auditing Web Search Results Related to the 2020 U.S. Presidential Primary Elections Across Six Search Engines

2021 ◽  
pp. 089443932110068
Author(s):  
Aleksandra Urman ◽  
Mykola Makhortykh ◽  
Roberto Ulloa
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Large Scale ◽  
Web Search ◽  
Primary Elections ◽  
Virtual Agents ◽  
Search Results ◽  
Presidential Primary ◽  
Large Scale Analysis ◽  
Algorithmic Information

We examine how six search engines filter and rank information in relation to the queries on the U.S. 2020 presidential primary elections under the default—that is nonpersonalized—conditions. For that, we utilize an algorithmic auditing methodology that uses virtual agents to conduct large-scale analysis of algorithmic information curation in a controlled environment. Specifically, we look at the text search results for “us elections,” “donald trump,” “joe biden,” “bernie sanders” queries on Google, Baidu, Bing, DuckDuckGo, Yahoo, and Yandex, during the 2020 primaries. Our findings indicate substantial differences in the search results between search engines and multiple discrepancies within the results generated for different agents using the same search engine. It highlights that whether users see certain information is decided by chance due to the inherent randomization of search results. We also find that some search engines prioritize different categories of information sources with respect to specific candidates. These observations demonstrate that algorithmic curation of political information can create information inequalities between the search engine users even under nonpersonalized conditions. Such inequalities are particularly troubling considering that search results are highly trusted by the public and can shift the opinions of undecided voters as demonstrated by previous research.

EVA 2.0: Emotional and rational multimodal argumentation between virtual agents

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Niklas Rach ◽  
Klaus Weber ◽  
Yuchi Yang ◽  
Stefan Ultes ◽  
Elisabeth André ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
User Feedback ◽  
Virtual Agents ◽  
Multi Agent System ◽  
Dialogue Game ◽  
Multi Agent ◽  
The Individual ◽  
Minimal Bias ◽  
Intuitive Interface ◽  
Emotional Level

Abstract Persuasive argumentation depends on multiple aspects, which include not only the content of the individual arguments, but also the way they are presented. The presentation of arguments is crucial – in particular in the context of dialogical argumentation. However, the effects of different discussion styles on the listener are hard to isolate in human dialogues. In order to demonstrate and investigate various styles of argumentation, we propose a multi-agent system in which different aspects of persuasion can be modelled and investigated separately. Our system utilizes argument structures extracted from text-based reviews for which a minimal bias of the user can be assumed. The persuasive dialogue is modelled as a dialogue game for argumentation that was motivated by the objective to enable both natural and flexible interactions between the agents. In order to support a comparison of factual against affective persuasion approaches, we implemented two fundamentally different strategies for both agents: The logical policy utilizes deep Reinforcement Learning in a multi-agent setup to optimize the strategy with respect to the game formalism and the available argument. In contrast, the emotional policy selects the next move in compliance with an agent emotion that is adapted to user feedback to persuade on an emotional level. The resulting interaction is presented to the user via virtual avatars and can be rated through an intuitive interface.

scholarly journals Using virtual agents to increase physical activity in young children with the virtual fitness buddy ecosystem: Study protocol for a cluster randomized trial

2020 ◽  
Vol 99 ◽  
pp. 106181
Author(s):  
Lindsay Hahn ◽  
Michael D. Schmidt ◽  
Stephen L. Rathbun ◽  
Kyle Johnsen ◽  
James J. Annesi ◽  
...  
Keyword(s):  
Physical Activity ◽  
Young Children ◽  
Randomized Trial ◽  
Study Protocol ◽  
Cluster Randomized Trial ◽  
Virtual Agents ◽  
Cluster Randomized

A Transparent and Decentralized Model of Perception and Action for Intelligent Virtual Agents

2014 ◽  
Vol 23 (04) ◽  
pp. 1460020 ◽  
Author(s):  
George Anastassakis ◽  
Themis Panayiotopoulos
Keyword(s):  
Knowledge Representation ◽  
Virtual Environment ◽  
Virtual World ◽  
Perception And Action ◽  
Virtual Agents ◽  
Virtual Agent ◽  
Complex Interactions ◽  
Intelligent Virtual Agents ◽  
Decentralized Model ◽  
Over Time

Intelligent virtual agent behaviour is a crucial element of any virtual environment application as it essentially brings the environment to life, introduces believability and realism and enables complex interactions and evolution over time. However, the development of mechanisms for virtual agent perception and action is neither a trivial nor a straight-forward task. In this paper we present a model of perception and action for intelligent virtual agents that meets specific requirements and can as such be systematically implemented, can seamlessly and transparently integrate with knowledge representation and intelligent reasoning mechanisms, is highly independent of virtual world implementation specifics, and enables virtual agent portability and reuse.

Intersectoral information and intellectual model of integration of information flows of interregional level subjects

2021 ◽  
pp. 45-56
Author(s):  
G. A. Galkin ◽  
◽  
V. V. Zubkov ◽  
N. F. Sirina ◽  
◽  
...  
Keyword(s):  
Large Scale ◽  
Virtual Agents ◽  
Information Flows ◽  
Business Associations ◽  
Distributed Information ◽  
Intellectual Content ◽  
Software Products ◽  
Transport Services ◽  
Marine Traffic ◽  
Intellectual System

Modern challenges actualize the search for transformation of management and interaction mechanisms and tools for determining and making optimal managerial decisions based on quota (distributed) information and intellectual content, which create conditions for the implementation of a systematic method for solving the problem of creating a large-scale and multifunctional complex of information and intellectual management and interaction systems. In this paper, the principles of building an intersectoral information and intellectual model of integration of information flows of subjects of the interregional level are considered. The construction of the model is based on the principles of information and intellectual interaction in the segment of the information economy of social and marketing cooperation. The components of the model formation methodology are presented. The system of component-methodology assumes concentration in one perimeter of information flows coming from the integrating information systems of subjects of the intersectoral, interregional level, federal regulators and business associations, using the information technology «big data». The model of integration of information flows accumulates and concentrates information knowledge in a single transport and information space and is a quota-based information and intellectual system, the structure of which reflects the coordinated interactions of virtual agents. The subjects of accumulation and concentration of information knowledge are virtual agents (integrating information and intellectual systems) of regulators, subjects and business associations. The creation of such virtual agents is based on the multiagent construction principle. Virtual agents are a new category of software products that operate in information and intellectual environment on behalf of the user. The principles of virtual agent modeling and methodology for constructing the model were used in creating software products «Electronic Service of integrated transport services» and «Multiagent intellectual system for management of transport services in rail-marine traffic», which were registered by the state.

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