Predictive and Alert Systems – RITMO
Humans are superior to computers and robots when it comes to anticipating future events by applying multimodal sensing together with learned knowledge in choosing the best actions. Are we able to transfer these prediction skills into intelligent systems and also apply that knowledge in how the systems interact with human users?
That is what we would like to address in one or more mater projects; through collaboration with researchers in cognitive psychology who we collaborate with in the RITMO Centre of Excellence, we aim at applying recent understanding within the field to develop models to be applied in perception-action loops of future intelligent systems including smartphones and robots.
The project is concerned with introducing new technology by applying cognitive psychology concepts for shifting between instinctive reactions and slower well-reasoned response using prediction mechanisms. Human capabilities like prediction and instinctive reaction – even in a complex situation, are features that are important for humans as for future robots to be able to offer intelligent and effective human interaction. Developing such capabilities within robotics and smartphones is the overall goal of this project. This includes demonstrating how a system with the capability of being alert would increase user friendliness.
Cognitive control has been explored in cognitive psychology and neuroscience by referring to processes that allow information processing and behaviour to vary adaptively from moment to moment depending on current goals, rather than remaining rigid and inflexible. Cognitive control enables humans to flexibly switch between different thoughts and actions. Models with two modes of thought have been proposed in psychology; one being fast and instinctive and another being slower and with more reasoning involved (Kahneman, 2011). One may think that the latter is to be preferred but humans almost entirely use the instinctive one in their daily life. That is, we do not think much about what to do when we walk or cycle. The benefit is that we do tasks effectively and with little cognitive effort. However, if we fail in doing something, we have to slow down and try again with more reasoning until can manage it. Next time we may be able to do the same task in an intuitive way using that earlier learned knowledge (Li, 2016).
[Kahneman 2011] D. Kahneman, “Thinking, Fast and Slow”, Penguin UK, 2011.
[Li 2016] T. H. S. Li et al., "Robots That Think Fast and Slow: An Example of Throwing the Ball Into the Basket," in IEEE Access, vol. 4, no. , pp. 5052-5064, 2016.
The tasks of the project:
- Get an overview of theory behind the two model system in humans and work undertaken on emulating it in artificial systems.
- Define an own experimental setup to work on developing a demonstrator of the thinking and fast and slow concept.
- Compare various implementations of the system.
- Write master thesis report
The RITMO - Centre for Interdisciplinary Studies of Rhythm, Time and Motion started in 2018. Researchers in the network come from the ROBIN group (Informatics), FRONT Neurolab (Psychology), and the Department of Musicology, and have access to state-of-the-art laboratories.