Otto Lappi
Biographic Data
| ID | 5816281 |
|---|---|
| NAME | Otto Lappi |
| GIVEN NAMES | Otto |
| FAMILY NAME | Lappi |
| SIGNATURE | LAPPI O |
| AFFILIATIONS | University of Helsinki |
| ORCID | 0000-0002-7996-7665 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 4 |
| WORKS AS AUTHOR | 5 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2016 |
| LATEST PUBLICATION YEAR | 2021 |
| H-INDEX | 1 |
The link between flow and performance is moderated by task experience
Flow is an intrinsically motivating (i.e. ‘autotelic’) psychological state of complete absorption in moment-to-moment activity that can occur when one performs a task whose demands match one's skill-level. Flow theory proposes that Flow causally leads to better performance, but empirical evidence for this assumption is mixed. Recent evidence suggests that self-reported Flow may not be linked to performance-levels per se, but instead to deviations…
Action control, forward models and expected rewards
The fundamental cognitive problem for active organisms is to decide what to do next in a changing environment. In this article, we analyze motor and action control in computational models that utilize reinforcement learning (RL) algorithms. In reinforcement learning, action control is governed by an action selection policy that maximizes the expected future reward in light of a predictive world model. In this paper we argue that RL provides a way…
From Fly Detectors to Action Control
According to radical enactivists, cognitive sciences should abandon the representational framework. Perceptuomotor cognition and action control are often provided as paradigmatic examples of nonrepresentational cognitive phenomena. In this article, we illustrate how motor and action control are studied in research that uses reinforcement learning algorithms. Crucially, this approach can be given a representational interpretation. Hence, reinforce…
Visuomotor control, eye movements, and steering
The authors present an approach to the coordination of eye movements and locomotion in naturalistic steering tasks. It is based on recent empirical research, in particular, on driver eye movements, that poses challenges for existing accounts of how we visually steer a course. They first analyze how the ideas of feedback and feedforward processes and internal models are treated in control theoretical steering models within vision science and engin…
On computational explanations
On computational explanations
Visuomotor control, eye movements, and steering
The authors present an approach to the coordination of eye movements and locomotion in naturalistic steering tasks. It is based on recent empirical research, in particular, on driver eye movements, that poses challenges for existing accounts of how we visually steer a course. They first analyze how the ideas of feedback and feedforward processes and internal models are treated in control theoretical steering models within vision science and engin…
The link between flow and performance is moderated by task experience
Flow is an intrinsically motivating (i.e. ‘autotelic’) psychological state of complete absorption in moment-to-moment activity that can occur when one performs a task whose demands match one's skill-level. Flow theory proposes that Flow causally leads to better performance, but empirical evidence for this assumption is mixed. Recent evidence suggests that self-reported Flow may not be linked to performance-levels per se, but instead to deviations…
Action control, forward models and expected rewards
The fundamental cognitive problem for active organisms is to decide what to do next in a changing environment. In this article, we analyze motor and action control in computational models that utilize reinforcement learning (RL) algorithms. In reinforcement learning, action control is governed by an action selection policy that maximizes the expected future reward in light of a predictive world model. In this paper we argue that RL provides a way…
From Fly Detectors to Action Control
According to radical enactivists, cognitive sciences should abandon the representational framework. Perceptuomotor cognition and action control are often provided as paradigmatic examples of nonrepresentational cognitive phenomena. In this article, we illustrate how motor and action control are studied in research that uses reinforcement learning algorithms. Crucially, this approach can be given a representational interpretation. Hence, reinforce…
Computer Science (4 works) · Psychology (4 works) · Artificial Intelligence (3 works) · Artificial Intelligence (3 works) · Social Psychology (3 works) · Action (physics) (2 works) · Cognition (2 works) · Cognitive science (2 works) · Control (management) (2 works) · Embodied and Extended Cognition (2 works)