Henrik Hautop Lund

Evolutionary robotics-a children's game

The authors explore the concept of development without programming by children. Especially, they look at the case of developing robot control systems. The evolutionary robotics approach has shown that in some cases, given a mathematically described fitness function, it is possible to achieve an automatic development of robot controllers. However, it is questionable how one is to construct the mathematical fitness function. So they applied an interactive genetic algorithm to the problem of developing robot controllers and achieved and evolutionary robotics approach that allows children without any programming knowledge to develop controller for LEGO robots. They used neural networks as robot controllers, and found that combining the interactive genetic algorithm with a kind of reinforcement learning-development at the evolutionary time scale combined with life-time development-reduces the development time drastically. Hence, they overcome one of the major drawbacks of the interactive genetic algorithm, namely the development time.

Physical and temporal scaling considerations in a robot model of cricket calling song preference

Behavioral experiments with crickets show that female crickets respond to male calling songs with syllable rates within a certain bandwidth only. We have made a robot model in which we implement a simple neural controller that is less complex than the controllers traditionally hypothesized for cricket phonotaxis and syllable rate preference. The simple controller, which had been successfully used with a slowed and simplified signal, is here demonstrated to function, using songs with identical parameters to those found in real male cricket song, using an analog electronic model of the peripheral auditory morphology of the female cricket as the sensor. We put the robot under the same experimental conditions as the female crickets, and it responds with phonotaxis to calling songs of real male Gryllus bimaculatus. Further, the robot only responds to songs with syllable rates within a bandwidth similar to the bandwidth found for crickets. By making polar plots of the heading direction of the robot, we obtain behavioral data that can be used in statistical analyses. These analyses show that there are statistically significant differences between the behavioral responses to calling songs with syllable rates within the bandwidth and calling songs with syllable rates outside the bandwidth. This gives the verification that the simple neural control mechanism (together with morphological auditory matched filtering) can account for the syllable rate preference found in female crickets. With our robot system, we can now systematically explore the mechanisms controlling recognition and choice behavior in the female cricket by experimental replication.

Evolving and Breeding Robots

Our experiences with a range of evolutionary robotic experiments have resulted in major changes to our set-up of artificial life experiments and our interpretation of observed phenomena. Initially, we investigated simulation-reality relationships in order to transfer our artificial life simulation work with evolution of neural network agents to real robots. This is a difficult task, but can, in a lot of cases, be solved with a carefully built simulator. By being able to evolve control mechanisms for physical robots, we were able to study biological hypotheses about animal behaviours by using exactly the same experimental set-ups as were used in the animal behavioural experiments. Evolutionary robotic experiments with rats open field box experiments and chick detours show how evolutionary robotics can be a powerful biological tool, and they also suggest that incremental learning might be fruitful for achieving complex robot behaviour in an evolutionary context. However, it is not enough to evolve controllers alone, and we argue that robot body plans and controllers should co-evolve, which leads to an alternative form of evolvable hardware. By combining all these experiences, we reach breeding robotics. Here, children can, as breeders, evolve e.g. LEGO robots through an interactive genetic algorithm in order to achieve desired behaviours, and then download the evolved behaviours to the physical (LEGO) robots.

Robot soccer in education

The educational experiences from using robot soccer in computer science courses are outlined. The educational approach can be termed guided constructionism and it differs from traditional (pure) constructionism, which can be termed unguided constructionism, by combining hands-on experience with lecturing and guidance. We believe that some essential arguments need to be taught through lecturing and guidance, but also find it essential for the students to actively participate in our robot soccer competitions when the aim is to educate the students to be able to produce real-world applications when graduating from the university. In the computer science courses, the students were taught to work with robot soccer players with pre-defined robot morphology, with modifiable robot morphology and with robot team play. This should allow the students to learn (i) to manage the non-deterministic characteristics of the real environment, (ii) to integrate hardware and software solutions, and (iii) to manage collective ...

Arts, robots, and evolution as a tool for creativity

Publisher Summary In a human social context electronics has an inner and outer aspect—the software and the hardware, respectively. Moving from this background, the chapter investigates the relationship between art and technology. Technology or science produces deep changes in art. The chapter highlights the current relationship between art and electronics with respect to what is called “immaterial” and “material” art. The chapter emphasizes that while the exponential growth of electronics requires science-oriented artists, the explosion of technical knowledge also calls for teamwork. The chapter summarizes the current state of electronic art and outlines the characteristics of a new art form—“Alive Art”—characterized by perpetual change, interactivity, and vulnerability.

ALife Meets Web: Lessons Learned

Artificial life might come to play important roles for the World Wide Web, both as a source of new algorithmic paradigms and as a source of inspiration for its future development. New Web searching and managing techniques, based on artificial life principles, have been elicited by the striking similarities between the Web and natural environments. New Web interface designs, based on artificial life techniques, have resulted in increased aesthetic appeal, smart animations, and clever interactive rules. In this paper we exemplify these observations by surveying a number of meeting points between artificial life and the Web. We touch on a few implementation issues and attempt to draw some lessons to be learned from these early experiences.

Embodied Artificial Life

A characteristic of a mature scientific field is its ability to generate scientific debates. Just think of Watson and Crick’s DNA discovery in the 1950s. Or what about the engineering achievement of constructing the Deep Blue computer that defeated the world champion chess player? Certainly, these advances have raised debates that go far beyond the boundaries of the fields of genetics and engineering. Without trying to compare to these great achievements, one can, however, note that, likewise, several areas within the artificial life field are able to raise debates outside the artificial life community. One of these areas is the artificial life approach to robotics. For example, a number of biologists accept robots as a tool to verify (or falsify) their hypotheses about animal control mechanisms, which are based on animal behavioral experiments. Often, researchers do animal behavior experiments and, based on these experiments, come up with hypotheses about the animal control mechanism. These hypotheses can then be verified or falsified by building an adequate robot, implementing the hypothesized control mechanism, and then observing if it can account for the behavior. If not, then biologists will go back to the animal lab and continue their behavioral experiments with the animals to come up with new, modified hypotheses. The majority of biologists might not accept this methodology, but the important fact is that the debate continues. The debate concerns the reliability of a robot as a model of the animal under study. In parallel, the artificial life community enjoys its own, similar debate: Can simulation of the real world be reliable, or is embodiment a necessity in order to gain understanding about life? The discussion about simulation versus embodiment is by no means new, and actually many researchers in both “camps” have been players in the other. For instance, some of artificial intelligence’s great theoreticians have previously tried to build robots. In the late 1950s, Minsky and others tried to build a ball-catching robot (derived from the initial wish to build a Ping-Pong-playing robot), and in the early 1970s, McCarthy tried to build an assembly robot (to assemble a television kit) [4]. Neither of the projects succeeded, and as is well known, both researchers have moved away from embodied artificial intelligence. A typical argument for going toward simulation has been that building real robots (apart from being difficult) is largely a question of technology: Intelligence could be implemented as a suitable information-processing system running

Ola—what goes up must fall down: emergent Mexican wave behavior

We made a LEGO Mindstorms robot soccer model using a distributed behaviour-based system, which was showcased at RoboCup98 during the soccer World Cup in France 1998. To put the robot soccer game into an appropriate context, we also constructed a stadium out of LEGO pieces, including stadium lights, rolling commercials, moving cameras projecting images onto big screens, a scoreboard and approximately 1500 small LEGO spectators who did the “Mexican wave” as seen in soccer stadiums. These devices were controlled using the LEGO Dacta Control Lab system and the LEGO CodePilot system that allow programming motor reactions which can be based on sensor inputs. The wave of the LEGO spectators was made using the principle ofemergent behaviour. There was no central control of the wave, but it emerges from the interaction between small units of spectators with a local feedback control.

Robot-Animal Interaction

It is described how autonomous robots can be a powerful tool for verifying biological hypotheses. One can implement a biological hypothesis on a robot, put the robot under same experimental conditions as an animal in biological experiments, and then verify whether the implemented hypothesis holds, e.g. can account for the behaviour observed in the animal. Here, it is shown with the example of cricket phonotaxis. The robot is built with a specific auditory mechanism that is hypothesised to be the basis for cricket phonotaxis. When real male crickets are placed in an arena, the robot will perform phonotaxis as soon as the male crickets start to sing the calling song.