| 1. |
- Biro, Zoltan, et al.
(författare)
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Evolution of visually-guided approach behaviour in recurrent artificial neural network robot controllers
- 1998
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Analysis of internal structures of embodied and situated agents may provide insights into the mechanisms underlying adaptive behaviour. This paper is concerned with the evolution and analysis of visually-guided approach behaviour in a simulated robotic agent controlled by a recurrent artificial neural network, whose connection weights have been evolved using evolutionary algorithms. Analysis of the evolved behaviours and their network-internal mechanisms reveals a behavioural structure and organization resembling a Brooksian subsumption architecture. The task decomposition, as well as the resulting individual behaviours and their integration, however, are realized as network-internal state space dynamics, evolved in the course of agent-environment interaction, i.e. with a minimum of designer intervention.
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| 2. |
- Niklasson, Lars, et al.
(författare)
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Lärande Datorer : Utopi eller Verklighet?
- 1996
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Rapport (populärvet., debatt m.m.)abstract
- Denna populärvetenskapliga rapport ger en kort introduktion till självlärande artificiella neurala nätverk, samt sätter dem i relation till den science fiction-version som ges på TV och film.
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| 3. |
- Sharkey, Noel E., et al.
(författare)
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A consideration of the biological and psychological foundations of autonomous robotics
- 1998
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Ingår i: Connection science (Print). - Skövde : University of Skövde. - 0954-0091 .- 1360-0494. ; 10:3-4, s. 361-391
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The new wave of robotics aims to provide robots with the capacity to learn, develop and evolve in interaction with their environments using biologically inspired techniques. This work is placed in perspective by considering its biological and psychological basis with reference to some of the grand theorists of living systems. In particular, we examine what it means to have a body by outlining theories of the mechanisms of bodily integration in multicellular organisms and their means of solidarity with the environment. We consider the implications of not having a living body for current ideas on robot learning, evolution, and cognition and issue words of caution about wishful attributions that can smuggle more into observations of robot behaviour than is scientifically supportable. To round off the arguments we take an obligatory swipe at ungrounded artificial intelligence but quickly move on to assess physical grounding and embodiment in terms of the rooted cognition of the living.
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| 4. |
- Sharkey, Noel E., et al.
(författare)
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Life, Mind and Robots : The Ins and Outs of Embodied Cognition
- 1999
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Many believe that the major problem facing traditional artificial intelligence (and the functional theory of mind) is how to connect intelligence to the outside world. Some turned to robotic functionalism and a hybrid response, that attempts to rescue symbolic functionalism by grounding the symbol system with a connectionist hook to the world. Others turned to an alternative approach, embodied cognition, that emerged from an older tradition in biology, ethology, and behavioural modelling. Both approaches are contrasted here before a detailed exploration of embodiment is conducted. In particular we ask whether strong embodiment is possible for robotics, i.e. are robot "minds'' similar to animal minds, or is the role of robotics to provide a tool for scientific exploration, a weak embodiment? We define two types of embodiment, Loebian and Uexküllian, that express two different views of the relation between body, mind and behaviour. It is argued that strong embodiment, either Loebian or Uexküllian, is not possible for present day robotics. However, weak embodiment is still a useful way forward.
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| 5. |
- Ziemke, Tom
(författare)
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Adaptive Behavior in Autonomous Agents
- 1998
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Ingår i: Presence - Teleoperators and Virtual Environments. - Skövde : University of Skövde. - 1054-7460 .- 1531-3263. ; 7:6, s. 564-587
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This paper gives an overview of the bottom-up approach to artificial intelligence (AI), commonly referred to as behavior-oriented AI. The behavior-oriented approach, with its focus on the interaction between autonomous agents and their environments, is introduced by contrasting it with the traditional approach of knowledge-based AI. Different notions of autonomy are discussed, and key problems of generating adaptive and complex behavior are identified. A number of techniques for the generation of behavior are introduced and evaluated regarding their potential for realizing different aspects of autonomy as well as adaptivity and complexity of behavior. It is concluded that in order to realize truly autonomous and intelligent agents, the behavior-oriented approach will have to focus even more on life-like qualities in both agents and environments.
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| 6. |
- Ziemke, Tom, et al.
(författare)
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Connectionist Models for the Detection of Oil Spills from Doppler Radar Imagery
- 1995
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This paper reports on the results of a project investigating the potential of applying artificial neural networks to the problem of detecting oil spills on basis of the radar backscatter signals from a sea clutter environment illuminated by a Doppler radar. Recurrent backpropagation models which were found to exhibit satisfactory performance, superior to that of feed-forward networks, are discussed and analysed in particular.
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| 7. |
- Ziemke, Tom, et al.
(författare)
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Oil Spill Detection : A Case Study of Recurrent Artificial Neural Networks
- 1997
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This paper summarizes and analyzes the results of a case study of artificial neural networks for the detection of oil spills from radar imagery, which has been carried as a joint project between the Connectionist Research Group, University of Skövde, and Ericsson Microwave Systems AB, Mölndal, Sweden.
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| 8. |
- Ziemke, Tom, et al.
(författare)
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Oil Spill Detection from Doppler Radar Imagery using Artificial Neural Networks
- 1995
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This paper reports on results of an ongoing project investigating the application of artificial neural networks (ANNs) to the classification/ cartography of sea clutter environments, and in particular the detection of oil spills, on the basis of their radar backscatter signals.
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| 9. |
- Ziemke, Tom
(författare)
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Radar Image Segmentation using Recurrent Artificial Neural Networks
- 1996
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This paper discusses the application of artificial neural networks to the segmentation of Doppler radar images, in particular the detection of oil spills within sea environments, based on a classification of radar backscatter signals. Best results have been achieved with recurrent backpropagation networks of an architecture similar to that of Elman's Simple Recurrent Network. The recurrent networks are shown to be very robust to variations in both sea state (weather conditions) as well as illumination distance, and their performance is analysed in further detail.
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| 10. |
- Ziemke, Tom
(författare)
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Radar Image Segmentation using Second-Order Recurrent Networks
- 1996
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- A second-order recurrent artificial neural network architecture for the segmentation and integration of radar images is introduced in this paper. This architecture consists of two sub-networks: a function network that classifies radar measurements into four different categories of objects in sea environments (water, oil spills, land and boats), and a context network that dynamically computes the function network's input weights. It is shown that this mechanism allows networks to learn to solve the task through a dynamic adaptation of their weighting of different radar measurements.behaviour.
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