scholarly journals A Geometric Semantics for Dialogue Game Protocols for Autonomous Agent Interactions

2002 ◽  
Vol 52 (2) ◽  
pp. 187-204 ◽  
Author(s):  
Peter McBurney ◽  
Simon Parsons
Keyword(s):  
Autonomous Agent ◽  
Dialogue Game ◽  
Agent Interactions

Controlling an Autonomous Agent for Exploring Unknown Environments using Switching Prelearned Modules

2018 ◽  
Vol 138 (2) ◽  
pp. 157-164
Author(s):  
Takahito Hata ◽  
Masanori Suganuma ◽  
Tomoharu Nagao
Keyword(s):  
Autonomous Agent ◽  
Unknown Environments

Dynamic Control and Formal Models of Multi-Agent Interactions and Behaviors

2003 ◽  
Author(s):  
Jeff Coble ◽  
Larry Roszman ◽  
Tiffany Frazier
Keyword(s):  
Dynamic Control ◽  
Formal Models ◽  
Agent Interactions ◽  
Multi Agent ◽  
And Behaviors

scholarly journals Towards alignment strategies in human-agent interactions based on measures of lexical repetitions

2021 ◽  
Author(s):  
Guillaume Dubuisson Duplessis ◽  
Caroline Langlet ◽  
Chloé Clavel ◽  
Frédéric Landragin
Keyword(s):  
Agent Interactions ◽  
Human Agent

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 Agent Based Models of Polymicrobial Biofilms and the Microbiome—A Review

2021 ◽  
Vol 9 (2) ◽  
pp. 417
Author(s):  
Sherli Koshy-Chenthittayil ◽  
Linda Archambault ◽  
Dhananjai Senthilkumar ◽  
Reinhard Laubenbacher ◽  
Pedro Mendes ◽  
...  
Keyword(s):  
Species Interactions ◽  
Computational Models ◽  
Human Microbiome ◽  
Agent Based Modeling ◽  
Autonomous Agent ◽  
Agent Based Models ◽  
Agent Based ◽  
Complex Interactions ◽  
Mucosal Surfaces ◽  
Living Organisms

The human microbiome has been a focus of intense study in recent years. Most of the living organisms comprising the microbiome exist in the form of biofilms on mucosal surfaces lining our digestive, respiratory, and genito-urinary tracts. While health-associated microbiota contribute to digestion, provide essential nutrients, and protect us from pathogens, disturbances due to illness or medical interventions contribute to infections, some that can be fatal. Myriad biological processes influence the make-up of the microbiota, for example: growth, division, death, and production of extracellular polymers (EPS), and metabolites. Inter-species interactions include competition, inhibition, and symbiosis. Computational models are becoming widely used to better understand these interactions. Agent-based modeling is a particularly useful computational approach to implement the various complex interactions in microbial communities when appropriately combined with an experimental approach. In these models, each cell is represented as an autonomous agent with its own set of rules, with different rules for each species. In this review, we will discuss innovations in agent-based modeling of biofilms and the microbiota in the past five years from the biological and mathematical perspectives and discuss how agent-based models can be further utilized to enhance our comprehension of the complex world of polymicrobial biofilms and the microbiome.

Host-Etiological Agent Interactions in Intranasally and Intraperitoneally Induced Cryptococcosis in Mice

1980 ◽  
Vol 29 (2) ◽  
pp. 633-641 ◽  
Author(s):  
Thuang S. Lim ◽  
Juneann W. Murphy ◽  
Larry K. Cauley
Keyword(s):  
Etiological Agent ◽  
Delayed Type Hypersensitivity ◽  
In Vivo Model ◽  
Spleen Cells ◽  
Polysaccharide Antigen ◽  
Cryptococcal Antigen ◽  
Agent Interactions ◽  
Growth Profiles ◽  
Host Parasite

Inbred CBA/J mice were used in developing a defined in vivo model for studying host-parasite relationships in cryptococcosis. Mice were infected either intranasally or intraperitoneally with 10 3 viable Cryptococcus neoformans cells. At weekly intervals over a 92-day period, C. neoformans growth profiles in the lungs, spleens, livers, and brains of the infected animals were determined. In addition, humoral and delayed-type hypersensitivity responses and cryptococcal antigen levels were assayed in these mice. Intranasally infected mice developed strong delayed-type hypersensitivity reactions in response to cryptococcal culture filtrate (CneF) antigen, and there was good correlation between acquisition of delayed-type hypersensitivity and the reduction of C. neoformans cell numbers in infected tissues. In contrast, intraperitoneally infected mice displayed greater numbers of C. neoformans cells in tissues and had somewhat suppressed delayed-type hypersensitivity responses to CneF antigen. Anticryptococcal antibodies were not detected in intranasally or intraperitoneally infected mice, but cryptococcal polysaccharide antigen titers were relatively high in both groups. The transfer of sensitized spleen cells from intranasally infected mice to syngeneic naive recipient mice resulted in the transfer of delayed-type hypersensitivity responsiveness to cryptococcal antigen in the recipients. The intranasally induced infection in mice was similar to the naturally acquired infection in humans; therefore we are proposing that this murine-cryptococcosis model would be useful in gaining a greater understanding of host-etiological agent relationships in this disease.

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