WHO WE ARE ::

Bryan Berend
Yasaman Kazerooni
Emmanuel Kumar
Craig Sanders
Mehgha Shyam

research assistants

COLLABORATORS ::

universität mainz
university of birmingham
university of massachusetts
universität marburg
nasa ames
hci group
national science foundation
universität
potsdam
Jeshua Bratman
Monica Eboli
Xiaoxiao Guo
Nan Jiang
John Laird

Satinder Singh

michigan computer science
michigan linguistics
Marc Berman
university of toronto
michigan psychology

RECENT PAPERS

Quick links below; for more publications and citation information, click here.

to appear
Topics in Cognitive Science
The adaptive nature of eye-movements in linguistic tasks: How payoff and architecture shape speed-accuracy tradeoffs

2012
Proceedings of the IEEE Conference on Development and Learning
Optimal rewards in multiagent teams

2012
Proceedings of the11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2012)
Strong Mitigation: Nesting Search for Good Policies Within Search for Good Reward

2011
Memory & Cognition
Resolving semantic and proactive interference in memory over the short-term

2011
Journal of Experimental Psychology: Learning, Memory, and Cognition
In search of on-line locality effects in sentence comprehension

2011
Proceedings of AAAI-2011 (Conference of the Association for the Advancement Artificial Intelligence)
Optimal rewards versus leaf-evaluation heuristics in planning agents

2011
Cognition
Divergent effects of different positive emotions on moral judgement

2010
Proceedings of NELS 41: Conference of the North East Linguistics Society
Featural analysis and short-term memory retrieval in on-line parsing: Evidence for syntactic, but not phonological, similarity-based interference

2010
Proceedings of the 10th International Conference on Cognitive Modeling
A new approach to exploring language emergence as boundedly optimal control in the face of environmental and cognitive constraints

2010
IEEE Transactions on Autonomous Mental Development
Instrinsically motivated reinforcement learning: An evolutionary perspective

2010
Advances in Neural Information Processing Systems
Reward design via online gradient ascent

2010
Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence
Variance-based rewards for approximate Bayesian reinforcement learning

2010
International Conference on Machine Learning
Internal rewards mitigate agent boundedness

2010
Language and Cognitive Processes
Short-term forgetting in sentence comprehension: Crosslinguistic evidence from verb-final structures

2009
Journal of Experimental Psychology: Learning, Memory, & Cognition
In search of decay in verbal short-term memory

2009
Psychological Review
Rational adaptation under task and processing constraints: Implications for testing theories of cognition and action

2009
Proceedings of the Annual Conference of the Cognitive Science Society
Where do rewards come from?

2008
Annual Review of Psychology
The mind and brain of short-term memory

2008
Cognitive Science
Processing polarity: How the ungrammatical intrudes on the grammatical

Welcome to the Language and Cognitive Architecture Lab at the University of Michigan.

 

about our research

The goal of our research is to develop theories of language, thought, and action—theories capturing the adaptive nature of human behavior, and grounded in integrated architectures that explain how the computational subsystems of the mind and brain work together.

An over-arching theoretical principle guiding much of our work is bounded optimality—the idea that behavior is the adaptive response to the joint constraints of the biological processing architecture and the external probabilistic environment.

The specific topics we focus on are the (boundedly optimal) adaptive control of perceptual, motor, cognitive and linguistic processes; language processing (especially the role of working memory in sentence comprehension and production); flexible artificial intelligence (AI) agents and reinforcement learning; and the interaction of cognition and emotion (especially mirth and other positive emotions).

The work makes contact with several areas of cognitive science, including psycholinguistics, linguistic theory, cognitive psychology, cognitive modeling, human-computer interaction, cognitive architectures, and reinforcement learning. It is highly collaborative (see left). To learn more about the research, click on the topics at left, or the questions below.