Iain D. Couzin
Department of Ecology & Evolutionary Biology, Princeton University, USA
Sensory networks and distributed cognition in animal groups
Understanding how social influence shapes biological processes is a central challenge in contemporary science,
essential for achieving progress in a variety of fields ranging from the organization and evolution of coordinated
collective action among cells, or animals, to the dynamics of information exchange in human societies.
Using an integrated experimental and theoretical approach, I will address how, and why, animals coordinate behavior.
In many schooling fish and flocking birds, decision-making by individuals is so integrated that it has been associated
with the concept of a “collective mind”. As each organism has relatively local sensing ability, coordinated animal groups
have evolved collective strategies that allow individuals, through the dynamical properties of social transmission, to access
higher-order capabilities at the group level. However we know very little about the relationship between individual and collective
cognition. A major limitation is that it has not been possible to observe directly the pathways of communication, and social
networks are typically based on proxies such as spatial proximity among organisms. I will demonstrate new imaging technology
that allows us to reconstruct (automatically) the dynamic, time-varying networks that correspond to the visual cues employed
by organisms when making movement decisions. Sensory networks are shown to provide a much more accurate representation of how
social influence propagates in groups, and one that cannot be captured correctly by social networks based on spatial proximity
(regardless of how they are parameterized). I investigate the coupling between spatial and information dynamics in groups and
reveal that emergent problem solving is the predominant mechanism by which mobile groups sense, and respond to complex
environmental gradients. This distributed sensing requires rudimentary cognition and is shown to be highly robust to noise.
I will also demonstrate the critical role uninformed individuals (those who have no information about the feature upon which
a collective decision is being made) play in fast,
and effective, democratic consensus decision-making in collectives.
Computational Thinking; Visualization; Modeling, Simulation
Iain Couzin is a Professor in the Department of Ecology and Evolutionary Biology at Princeton University.
Previously he was an Assistant Professor at Princeton University, a Royal Society University Research Fellow
in the Department of Zoology, University of Oxford, and Junior Research Fellow in the Sciences at Balliol College, Oxford.
His work aims to reveal the fundamental principles that underlie evolved collective behavior, and consequently his research includes the study of a wide range of biological systems, from cellular collectives to insect swarms, fish schools and human crowds. In recognition of his research he was recipient of a Searle Scholar Award in 2008, the Mohammed Dahleh Award in 2009, Popular Science Magazines “Brilliant 10” award in 2010,
PopTech Science and Public Leadership award in 2011 and National Geographic Emerging Explorer Award in 2012.
From Agents to Electronic Order
Trust, reputation, norms and organisations are all relevant to the
effective operation of open and dynamic multiagent systems. Inspired by
human systems, yet not constrained by them, these concepts provide a
means to establish a sense of order in computational environments (and
mixed human-machine ones). In this talk I will review previous work
across a range of areas in support of the need to develop theories and
systems that provide the computational analogue of common social
coordination mechanisms used by humans, in addition to those that might
only find favour in computational systems. I will focus on particular
examples that illustrate different approaches, including through the use
of norms and contracts, and suggest some key challenges that need to be
addressed to drive the field forward.
Michael Luck is Professor of Computer Science and Head of the School of
Natural and Mathematical Sciences at King's College London, where he
also works in the Agents and Intelligent Systems group, undertaking
research into agent technologies and intelligent systems. He is
Scientific Advisor to the Board for Aerogility.His work has sought to
take a principled approach to the development of practical agent
systems, and spans, among other areas, formal models for intelligent
agents and multi-agent systems, norms and institutions, trust and
reputation, application to bioinformatics and health, and deployment and
technology forecasting. He is a director of the International Foundation
for Autonomous Agents and Multi-Agent Systems (IFAAMAS), was a member of
the Executive Committee of AgentLink III, the European Network of
Excellence for Agent-Based Computing, having previously been the
Director of AgentLink II. He is an editorial board member of Autonomous
Agents and Multi-Agent Systems, the International Journal of
Agent-Oriented Software Engineering, Web Intelligence and Agent Systems,
and ACM Transactions on Autonomous and Adaptive Systems, as well as for
the SpringerBriefs in Intelligent Systems series. He was also general
co-chair of the Ninth International Conference on Autonomous Agents and
Multiagent Systems (AAMAS 2010), held in Toronto, Canada in May 2010.
Winner of 2014 ACM/SIGAI Autonomous Agents award
The selection committee for the ACM/SIGAI Autonomous Agents Research Award is pleased to announce that Prof. Michael Wellman of the University of Michigan is the recipient of the 2014 award.
Putting the Agent in Agent-Based Modeling
Michael P. Wellman is Professor of Computer Science & Engineering at the University of Michigan.
He received a PhD from the Massachusetts Institute of Technology in 1988 for his work in qualitative probabilistic reasoning and
decision-theoretic planning. From 1988 to 1992, Wellman conducted research in these areas at the USAF’s Wright Laboratory.
For the past 20+ years, his research has focused on computational market mechanisms for distributed decision making and electronic commerce.
As Chief Market Technologist for TradingDynamics, Inc. (now part of Ariba), he designed configurable auction technology for dynamic
business-to-business commerce. Wellman previously served as Chair of the ACM Special Interest Group on Electronic Commerce (SIGecom),
and as Executive Editor of the Journal of Artificial Intelligence Research.
He is a Fellow of the Association for the Advancement of Artificial Intelligence and the Association for Computing Machinery.