The ASTECCA laboratory studies Adaptive Strategic Thinking and Executive Control of Cognition and Affect.
Our approach is GAme ThEoretical, SOcio-Cognitive, Computational, and Ecologically Relevant (GATESOCCER). In our laboratory we conceptualize strategic thinking as an ensemble of mental processes employed by individuals in order to succeed in situations characterized by interdependence and uncertainty. We refer to these situations as games, in accord with the established terminology of game theory. Game players can be humans or artificial intelligence (AI) agents. They have short- and long-term interests, individual and social motives, and typically weigh the costs and benefits of engaging in cooperation and / or competition with other players. They learn and adapt their strategies as the games unfold.
In our research we aim to advance our understanding of how humans use their own minds while interacting with their environment and other intelligent agents. The concept of interaction (whether interpersonal, human-machine, or human-environment) is critical to our approach. We study how people develop cognitive strategies, how they infer their counterparts’ strategies, and how they maintain or switch strategies depending on the dynamics of their environments. We are particularly interested in discovering the environmental constraints and affordances as well as the cognitive mechanisms that explain how people develop or acquire strategies, how they persist in carrying out a successful strategy, and how they overcome either interference from the environment or the impulsive appeal of short-term rewards.
 The idea of humans as mind users was taken from James Reason’s book „The human contribution” (Reason, 2008).
ECOLE (Environmental COgnition and LEarning) is the translational branch of ASTECCA and aims to discover science- and education-based solutions to particular societal problems such as the climate change crisis.
- Focus on higher-order and interactive cognition:
- Human-technology teaming, interpersonal and human-machine trust
- Peer-assisted learning, collective intelligence, and effort coordination
- Interactive decision making, problem solving, and executive control
- Focus on modeling the human mind and mimicking human behavior:
- The Common Model of Cognition, cognitive architectures (ACT-R, Soar)
- Interactive intelligent agents
- Attentional control in semi-structured ecological settings
- Cognitive effort avoidance in individual and group settings
- Human-machine forecasting
- Brain bases of learning
- Learning acceleration under conditions of brain stimulation