Netherlands

In this talk, I will present our work toward building Socially Interactive Agent SIA, that is agent able to be socially aware, interact with human partners, but also adapt its behaviors to favor user’s engagement during the interaction. During an interaction, partners adapt their behaviors to each other. Adaptation can happen at different levels, such as at the linguistic one (choice of vocabulary, grammatical style), the behavior one (change of posture), etc. It can involve the choice of a given conversational strategy to manage user’s impression, or synchronization mechanisms (eg imitate a smile)… Lately we have developed three adaptation mechanisms that work on different levels: conversational strategy, nonverbal behaviors and multimodal signals. I will present the general framework on which these models have been built. As it interacts with a human partner, the agent learns to adapt to maximize the quality of the interaction. These models have been evaluated through a study involving visitors of a science museum. I will discuss the results of these studies. Touch is a modality that is not much considered in human-agent interaction. Social touch bares many functions during an interaction. A caress can convey comfort, a tap human’s attention, etc. We have been working on endowing an agent to respond to social touch by a human and to touch the human to convey different intentions and emotions. I will describe the decision model based on the emotional model FAtiMA we have developed.

ICAART 2022

Interacting with Socially Interactive Agents

**31st IEEE International Conference on Robot & Human Interactive Communication**
 This conference is a leading forum where state-of-the-art innovative results, the latest developments as well as future perspectives relating to robot and human interactive communication are presented and discussed.
 
 The conference covers a wide range of topics related to Robot and Human Interactive Communication, involving theories, methodologies, technologies, empirical and experimental studies. Papers related to the study of robotic technology, psychology, cognitive science, artificial intelligence, human factors, ethics and policies, interaction-based robot design and other topics related to human-robot interaction are welcome.
 
 **CONFERENCE THEME:**
 Social, asocial, and antisocial robots
 
 Robots are starting to populate our lives: at work, in our homes, hotels, shops. However, not everybody is comfortable with robots finding a place in society. For example, people may be afraid that robots will replace humans in their jobs. This belief is exacerbated by the media that, on one side, raise expectations of robots’ capabilities, while amplifying fears and worries on the other side.
 
 In the next years, due to the increasing request for interaction with people in social environments, academic research and market analyses predict that robots will become more and more “social”. But, at the same time, robots may incur the risk of being perceived as “asocial” as their pervasiveness in everyday environments may become an obstacle to social interaction between humans. Or they may even be rejected as “antisocial” if researchers do not take care to develop robots that behave according to the customs and habits of the communities where they are expected to operate.
 
 To prevent this from happening, robotic researchers can no longer take the luxury of being mere technicians. They must be capable of addressing all the challenges raised by future robot-populated communities in a multidisciplinary way. They need to share their knowledge with the public to make people aware of what robots really are, what expectations we can have from them, the risks we may incur, and the possible mitigation plans.
 
 While being open to any kind of contribution related to Human-Robot Interactive Communication, the RO-MAN 2022 conference will emphasize these aspects of robotic research. How can we create robots capable of being welcomed as our assistants and companions in society while, at the same time, not being perceived as “asocial” or “antisocial?” How can we create robots perceived as facilitators of the natural development of human beings and communities, rather than obstacles?
 
 Contributions from different disciplines, not exclusively related to technological development, will be welcomed as crucial to pave the way to global acceptance of future robots with an informed attitude.
 
 [![](https://assets.underline.io/uploads/markdown_image/1/image/af259abe105b3791c498ae1552d75710.png)](https://drive.google.com/file/d/18w73BZPB_JVOgcrcdZDqYpEupwVt4CnU/view?usp=sharing)

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IEEE RO-MAN 2022

31st IEEE International Conference on Robot & Human Interactive Communication
This conference is a leading forum where state-of-the-art innovative results, the latest developments as well as future perspectives relating to robot and human interactive communication are presented and discussed.

keynote

The purpose of the International Conference on Agents and Artificial Intelligence is to bring together researchers, engineers and practitioners interested in the theory and applications in the areas of Agents and Artificial Intelligence. Two simultaneous related tracks will be held, covering both applications and current research work. One track focuses on Agents, Multi-Agent Systems and Software Platforms, Distributed Problem Solving and Distributed AI in general. The other track focuses mainly on Artificial Intelligence, Knowledge Representation, Planning, Learning, Scheduling, Perception Reactive AI Systems, and Evolutionary Computing and other topics related to Intelligent Systems and Computational Intelligence. 
CONFERENCE AREAS 
1 . Agents 
2 . Artificial Intelligence

The purpose of the International Conference on Agents and Artificial Intelligence is to bring together researchers, engineers and practitioners interested in the theory and applications in the areas of Agents and Artificial Intelligence. Two simultaneous related tracks will be held, covering both applications and current research work. One track focuses on Agents, Multi-Agent Systems and Software Platforms, Distributed Problem Solving and Distributed AI in general. The other track focuses mainly on Artificial Intelligence, Knowledge Representation, Planning, Learning, Scheduling, Perception Reactive AI Systems, and Evolutionary Computing and other topics related to Intelligent Systems and Computational Intelligence.

Automation is a fundamental part of industry and our private lives. At Festo, our vision is to free humans from harming tasks – these might be mentally (by being boring and repetitive) or even physically harming. Today, one aspect of an automation solution is that it is engineered to a specific problem and environment and often does not interact actively with humans. For humans to naturally interact with machines, it is needed that the machines can react to changing tasks and environments. Here, AI-based solutions come into play and offer a solution. Mechanisms inspired by biology offer efficient solutions to many questions arising in this field. This keynote will show concrete challenges from within the industrial automation and the solutions Festo research came up with.

Bio-Inspired AI for Autonomous Systems

Robotic agents that can accomplish manipulation tasks with the competence of humans have been one of the grand research challenges for artificial intelligence (AI) and robotics research for more than 50 years. However, while the fields made huge progress over the years, this ultimate goal is still out of reach. I believe that this is the case because the knowledge representation and reasoning methods that have been proposed in AI so far are necessary but too abstract. In this talk I propose to address this problem by endowing robots with the capability to internally emulate and simulate their perception-action loops based on realistic images and faithful physics simulations, which are made machine-understandable by casting them as virtual symbolic knowledge bases. These capabilities allow robots to generate huge collections of machine-understandable manipulation experiences, which robotic agents can generalize into commonsense and intuitive physics knowledge applicable to open varieties of manipulation tasks. The combination of learning, representation, and reasoning will equip robots with an understanding of the relation between their motions and the physical effects they cause at an unprecedented level of realism, depth, and breadth, and enable them to master human-scale manipulation tasks. This breakthrough will be achievable by combining leading-edge simulation and visual rendering technologies with mechanisms to semantically interpret and introspect internal simulation data structures and processes. Robots with such manipulation capabilities can help us to better deal with important societal, humanitarian, and economic challenges of our aging societies.

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Bio-Inspired AI for Autonomous Systems

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Seeing is not Feeling the Touch from a Robot

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