Header logo is


2019


Life Improvement Science: A Manifesto
Life Improvement Science: A Manifesto

Lieder, F.

December 2019 (article) In revision

Abstract
Rapid technological advances present unprecedented opportunities for helping people thrive. This manifesto presents a road map for establishing a solid scientific foundation upon which those opportunities can be realized. It highlights fundamental open questions about the cognitive underpinnings of effective living and how they can be improved, supported, and augmented. These questions are at the core of my proposal for a new transdisciplinary research area called life improvement science. Recent advances have made these questions amenable to scientific rigor, and emerging approaches are paving the way towards practical strategies, clever interventions, and (intelligent) apps for empowering people to reach unprecedented levels of personal effectiveness and wellbeing.

re

Life improvement science: a manifesto DOI [BibTex]


no image
Doing More with Less: Meta-Reasoning and Meta-Learning in Humans and Machines

Griffiths, T. L., Callaway, F., Chang, M. B., Grant, E., Krueger, P. M., Lieder, F.

Current Opinion in Behavioral Sciences, 29, pages: 24-30, October 2019 (article)

Abstract
Artificial intelligence systems use an increasing amount of computation and data to solve very specific problems. By contrast, human minds solve a wide range of problems using a fixed amount of computation and limited experience. We identify two abilities that we see as crucial to this kind of general intelligence: meta-reasoning (deciding how to allocate computational resources) and meta-learning (modeling the learning environment to make better use of limited data). We summarize the relevant AI literature and relate the resulting ideas to recent work in psychology.

re

DOI [BibTex]

DOI [BibTex]


Cognitive Prostheses for Goal Achievement
Cognitive Prostheses for Goal Achievement

Lieder, F., Chen, O. X., Krueger, P. M., Griffiths, T. L.

Nature Human Behavior, 3, August 2019 (article)

Abstract
Procrastination and impulsivity take a significant toll on people’s lives and the economy at large. Both can result from the misalignment of an action's proximal rewards with its long-term value. Therefore, aligning immediate reward with long-term value could be a way to help people overcome motivational barriers and make better decisions. Previous research has shown that game elements, such as points, levels, and badges, can be used to motivate people and nudge their decisions on serious matters. Here, we develop a new approach to decision support that leveragesartificial intelligence and game elements to restructure challenging sequential decision problems in such a way that it becomes easier for people to take the right course of action. A series of four increasingly more realistic experiments suggests that this approach can enable people to make better decisions faster, procrastinate less, complete their work on time, and waste less time on unimportant tasks. These findings suggest that our method is a promising step towards developing cognitive prostheses that help people achieve their goals by enhancing their motivation and decision-making in everyday life.

re

DOI [BibTex]

DOI [BibTex]


no image
Optimal Stair Climbing Pattern Generation for Humanoids Using Virtual Slope and Distributed Mass Model

Ahmadreza, S., Aghil, Y., Majid, K., Saeed, M., Saeid, M. S.

Journal of Intelligent and Robotics Systems, 94:1, pages: 43-59, April 2019 (article)

mg

DOI [BibTex]

DOI [BibTex]


no image
Resource-rational analysis: Understanding human cognition as the optimal use of limited computational resources

Lieder, F., Griffiths, T. L.

Behavioral and Brain Sciences, 43, E1, Febuary 2019 (article)

Abstract
Modeling human cognition is challenging because there are infinitely many mechanisms that can generate any given observation. Some researchers address this by constraining the hypothesis space through assumptions about what the human mind can and cannot do, while others constrain it through principles of rationality and adaptation. Recent work in economics, psychology, neuroscience, and linguistics has begun to integrate both approaches by augmenting rational models with cognitive constraints, incorporating rational principles into cognitive architectures, and applying optimality principles to understanding neural representations. We identify the rational use of limited resources as a unifying principle underlying these diverse approaches, expressing it in a new cognitive modeling paradigm called resource-rational analysis. The integration of rational principles with realistic cognitive constraints makes resource-rational analysis a promising framework for reverse-engineering cognitive mechanisms and representations. It has already shed new light on the debate about human rationality and can be leveraged to revisit classic questions of cognitive psychology within a principled computational framework. We demonstrate that resource-rational models can reconcile the mind's most impressive cognitive skills with people's ostensive irrationality. Resource-rational analysis also provides a new way to connect psychological theory more deeply with artificial intelligence, economics, neuroscience, and linguistics.

re

DOI [BibTex]

DOI [BibTex]


no image
A Robustness Analysis of Inverse Optimal Control of Bipedal Walking

Rebula, J. R., Schaal, S., Finley, J., Righetti, L.

IEEE Robotics and Automation Letters, 4(4):4531-4538, 2019 (article)

mg

DOI [BibTex]

DOI [BibTex]


no image
Rigid vs compliant contact: an experimental study on biped walking

Khadiv, M., Moosavian, S. A. A., Yousefi-Koma, A., Sadedel, M., Ehsani-Seresht, A., Mansouri, S.

Multibody System Dynamics, 45(4):379-401, 2019 (article)

mg

DOI [BibTex]

DOI [BibTex]


no image
Co-Contraction facilitates Body Stiffness Modulation during Swimming with Sensory Feedback in a Soft Biorobotic Physical Model

Jusufi, A., Vogt, D., Wood, R. J.

Integrative and Comparative Biology, 59(Supplement 1):E116-E116, Society of Integrative and Comparative Biology, McLean, VA, 2019 (article)

bio

DOI [BibTex]

DOI [BibTex]


no image
Birch tar production does not prove Neanderthal behavioral complexity

Schmidt, P., Blessing, M., Rageot, M., Iovita, R., Pfleging, J., Nickel, K. G., Righetti, L., Tennie, C.

Proceedings of the National Academy of Sciences (PNAS), 116(36):17707-17711, 2019 (article)

mg

DOI [BibTex]

DOI [BibTex]


A Rational Reinterpretation of Dual Process Theories
A Rational Reinterpretation of Dual Process Theories

Milli, S., Lieder, F., Griffiths, T. L.

2019 (article)

Abstract
Highly influential "dual-process" accounts of human cognition postulate the coexistence of a slow accurate system with a fast error-prone system. But why would there be just two systems rather than, say, one or 93? Here, we argue that a dual-process architecture might be neither arbitrary nor irrational, but might instead reflect a rational tradeoff between the cognitive flexibility afforded by multiple systems and the time and effort required to choose between them. We investigate what the optimal set and number of cognitive systems would be depending on the structure of the environment. We find that the optimal number of systems depends on the variability of the environment and the difficulty of deciding when which system should be used. Furthermore, when having two systems is optimal, then the first system is fast but error-prone and the second system is slow but accurate. Our findings thereby provide a rational reinterpretation of dual-process theories.

re

DOI [BibTex]

DOI [BibTex]

2009


no image
Adaptive Frequency Oscillators and Applications

Righetti, L., Buchli, J., Ijspeert, A.

The Open Cybernetics \& Systemics Journal, 3, pages: 64-69, 2009 (article)

Abstract
In this contribution we present a generic mechanism to transform an oscillator into an adaptive frequency oscillator, which can then dynamically adapt its parameters to learn the frequency of any periodic driving signal. Adaptation is done in a dynamic way: it is part of the dynamical system and not an offline process. This mechanism goes beyond entrainment since it works for any initial frequencies and the learned frequency stays encoded in the system even if the driving signal disappears. Interestingly, this mechanism can easily be applied to a large class of oscillators from harmonic oscillators to relaxation types and strange attractors. Several practical applications of this mechanism are then presented, ranging from adaptive control of compliant robots to frequency analysis of signals and construction of limit cycles of arbitrary shape.

mg

link (url) [BibTex]

2009


link (url) [BibTex]

2008


no image
Active tails enhance arboreal acrobatics in geckos

Jusufi, A., Goldman, D., Revzen, S., Full, R.

PNAS, 105(11):4215-4219, 2008 (article)

bio

link (url) [BibTex]

2008


link (url) [BibTex]


no image
Frequency analysis with coupled nonlinear oscillators

Buchli, J., Righetti, L., Ijspeert, A.

Physica D: Nonlinear Phenomena, 237(13):1705-1718, August 2008 (article)

Abstract
We present a method to obtain the frequency spectrum of a signal with a nonlinear dynamical system. The dynamical system is composed of a pool of adaptive frequency oscillators with negative mean-field coupling. For the frequency analysis, the synchronization and adaptation properties of the component oscillators are exploited. The frequency spectrum of the signal is reflected in the statistics of the intrinsic frequencies of the oscillators. The frequency analysis is completely embedded in the dynamics of the system. Thus, no pre-processing or additional parameters, such as time windows, are needed. Representative results of the numerical integration of the system are presented. It is shown, that the oscillators tune to the correct frequencies for both discrete and continuous spectra. Due to its dynamic nature the system is also capable to track non-stationary spectra. Further, we show that the system can be modeled in a probabilistic manner by means of a nonlinear Fokker–Planck equation. The probabilistic treatment is in good agreement with the numerical results, and provides a useful tool to understand the underlying mechanisms leading to convergence.

mg

link (url) DOI [BibTex]

link (url) DOI [BibTex]

2007


no image
iCub - The Design and Realization of an Open Humanoid Platform for Cognitive and Neuroscience Research

Tsagarakis, N., Metta, G., Sandini, G., Vernon, D., Beira, R., Becchi, F., Righetti, L., Santos-Victor, J., Ijspeert, A., Carrozza, M., Caldwell, D.

Advanced Robotics, 21(10):1151-1175, 2007 (article)

Abstract
The development of robotic cognition and the advancement of understanding of human cognition form two of the current greatest challenges in robotics and neuroscience, respectively. The RobotCub project aims to develop an embodied robotic child (iCub) with the physical (height 90 cm and mass less than 23 kg) and ultimately cognitive abilities of a 2.5-year-old human child. The iCub will be a freely available open system which can be used by scientists in all cognate disciplines from developmental psychology to epigenetic robotics to enhance understanding of cognitive systems through the study of cognitive development. The iCub will be open both in software, but more importantly in all aspects of the hardware and mechanical design. In this paper the design of the mechanisms and structures forming the basic 'body' of the iCub are described. The papers considers kinematic structures dynamic design criteria, actuator specification and selection, and detailed mechanical and electronic design. The paper concludes with tests of the performance of sample joints, and comparison of these results with the design requirements and simulation projects.

mg

link (url) DOI [BibTex]

2007


link (url) DOI [BibTex]