Michela Ponticorvo

Encoding geometric and non-geometric information: a study with evolved agents

Vertebrate species use geometric information and non-geometric or featural cues to orient. Under some circumstances, when both geometric and non-geometric information are available, the geometric information overwhelms non-geometric cues (geometric primacy). In other cases, we observe the inverse tendency or the successful integration of both cues. In past years, modular explanations have been proposed for the geometric primacy: geometric and non-geometric information are processed separately, with the geometry module playing a dominant role. The modularity issue is related to the recent debate on the encoding of geometric information: is it innate or does it depend on environmental experience? In order to get insight into the mechanisms that cause the wide variety of behaviors observed in nature, we used Artificial Life experiments. We demonstrated that agents trained mainly with a single class of information oriented efficiently when they were exposed to one class of information (geometric or non-geometric). When they were tested in environments that contained both classes of information, they displayed a primacy for the information that they had experienced more during their training phase. Encoding and processing geometric and non-geometric information was run in a single cognitive neuro-representation. These findings represent a theoretical proof that the exposure frequency to different spatial information during a learning/adaptive history could produce agents with no modular neuro-cognitive systems that are able to process different types of spatial information and display various orientation behaviors (geometric primacy, non-geometric primacy, no primacy at all).

Breedbot: an evolutionary robotics application in digital content

Purpose – This paper aims to describe an integrated hardware/software system based on evolutionary robotics and its application in an edutainment context.Design/methodology/approach – The system is based on a wide variety of artificial life techniques (artificial neural networks, genetic algorithms, user‐guided evolutionary design and evolutionary robotics). A user without any computer programming skill can determine the robots behavior in two different ways: artificial breeding or artificial evolution. Breedbot has been used as a didactic tool in teaching evolutionary biology and as a “futuristic” toy by several science centers. The digital side of Breedbot can be downloaded on the web site: www.isl.unina.it/breedbot Findings – The results in this pilot study suggest that using Breedbot in an educational context can be useful to improve learning in biology.Research limitations/implications – As this is a pilot study, one limitation is the small sample considered. The issue will be investigated further w...

Place cognition and active perception: a study with evolved robots

A study of place cognition and ‘place units’ in robots produced via artificial evolution is described. Previous studies have investigated the possible role of place cells as building blocks for ‘cognitive maps’ representing place, distance and direction. Studies also show, however, that when animals are restrained, the spatial selectivity of place cells is partially or completely lost. This suggests that the role of place cells in spatial cognition depends not only on the place cells themselves, but also on representations of the animals physical interactions with its environment. This hypothesis is tested in a population of evolved robots. The results suggest that successful place cognition requires not only the ability to process spatial information, but also the ability to select the environmental stimuli to which the agent is exposed. If this is so, theories of active perception can make a useful contribution to explaining the role of place cells in spatial cognition.

Breedbot: An Edutainment Robotics System to Link Digital and Real World

The paper describes Breedbot an edutainment software and hardware system that could be used to evolve autonomous agents in digital (software) world and to transfer the evolved minds in physical agents (robots). The system is based on a wide variety of Artificial Life techniques (Artificial Neural Networks, Genetic Algorithms, User Guided Evolutionary Design and Evolutionary Robotics). An user without any computer programming skill can determine the robot behaviour. Breedbot was used as a didactic tool in teaching Evolutionary Biology and as a futuristic toy by several Science Centers. The digital side of Breedbot is downloadable from www.isl.unina.it/breedbot.

Block Magic: A Prototype Bridging Digital and Physical Educational Materials to Support Children Learning Processes

Block Magic is a prototype for educational materials developed in a successful European research project under the framework of LLP-Comenius programme. It aimed at creating a bridge between physical manipulation and digital technology in education. Block Magic developed a functional prototypal system that enhanced the Logic Blocks Box. The prototype is made up of an active desk/board able to recognise concrete blocks equipped with the RFID passive tag and to communicate with a PC, an augmented reality system. Preliminary trials with Block Magic prototype were run in various schools in Germany, Greece, Italy and Spain, involving children aged 3 to 7. Results confirmed Block Magic educational platform effectiveness in educational context.

Towards Hyper Activity Books for Children. Connecting Activity Books and Montessori-like Educational Materials

In the first years of school, activity books and Montessori-like educational materials are widespread. They satisfy children’s precise psychological needs and result in funded educational practices based on game activity adopted by teachers. These materials are more effective for promoting learning if used in close interaction with an adult, they cannot be customised and the corrective feedback cannot be provided within the appropriate time frame. In this paper, we aim to overcome these limitations by exploiting a Technology Enhanced Learning (TEL) methodology to connect activity books and Montessori-like educational materials. We propose a general architecture for building hyper activity and exercise books called HAB, with three levels: multimedia, multimodality and computing; we describe a first implementation for validating this architecture, Block Magic, and outline development of the architecture under the INF@NZIA DIGI.Tales 3.6 project.

Digital and Multisensory Storytelling: Narration with Smell, Taste and Touch

Storytelling is a methodology which exploits narration to give meaning and sense to reality. It is omnipresent in human culture and it finds relevant application in pedagogy. Telling children stories helps them to understand the world, to learn about their culture, to vehiculate specific concepts, to reflect upon experiences. In an educational context, storytelling facilitates literacy, building shared meanings between adults and children. In recent years, thanks to technological development, digital tools have been included in the storytelling process, giving life to digital storytelling. A relevant feature of storytelling, both traditional and digital, is the chance to put together the cognitive dimension with the emotional one. For this reason it has been employed to gather attention from people with profound intellectual and mental disabilities too. The emotional dimension can be indeed useful for everyone, to attract children, to increase their motivation and to improve learning.

Tangible Interfaces for Cognitive Assessment and Training in Children: LogicART

This paper describes how to use tangible interfaces for cognitive assessment and training. Assessment and training are two fundamental phases in the learning process: assessment allows to gather information in order to identify the learner starting level and monitor progresses that training can lead to. Assessment uses tests, some of which are addressed to cognitive abilities. Many tests for cognitive abilities are based on verbal materials that are not suitable for population such as young children or people with special needs, and people with hard cognitive disabilities or sensory impairment. In these cases it would be more fruitable to use physical objects. This paper illustrates a hardware-software system, LogicART, that can be used in assessment and training of cognitive abilities, such as reasoning, memory, categorization, etc. exploiting physical materials augmented by RFID/NFC Technology. These materials, employed to study cognitive abilities, offer the advantage to stimulate multisensoriality and manipulation.

Place cognition as an example of situated cognition: a study with evolved agents.

The discovery of ‘place cells’ in the hippocampus of the rat was a seminal finding in the cognitive neuroscience of space processing (O’Keefe and Dostrovsky 1971). Place cells are pyramidal neurons in CA1 field of the dorsal hippocampus whose firing strongly depends on the rat’s location in a given environment. The discharge pattern of these cells is associated to a well-defined area of the environment where the unit maximally fires, the so-called ‘place field’. In O’Keefe’s words, a place cell is ‘‘a cell which constructs the notion of a place in an environment by connecting together several multi-sensory inputs each of which can be perceived when the animal is in a particular place in the environment’’ (1979, p. 425). Complementary to the information about position is the information about direction, provided by head direction cells, neurons that fire only when animals have their head in a certain direction. Recently, a new class of cells has been discovered whose firing depends on animal’s position. These are the grid cells (Fyhn et al. 2004) in dorsocaudal medial entorhinal cortex (dMEC), which are activated when the animal occupies a vertex of a regular grid that spans the entire surface of the environment. These findings support the hypothesis that in various areas of mammals’ brain there are topographic neural maps that converge to spatial representation: in the hippocampus whose basic unit is the place cell and in the dMEC whose basic unit is the grid cell. Both these cells share a property: their firing defines unambiguous position in space. The specific configuration of these cells builds an internal representation of the environment that allows the animal to know its position with respect to important locations, in other words represent the allocentric space. However, some experiments, specifically run on place cells, have shown that in some cases the selectivity of firing is partially or totally lost. Foster et al. (1989) investigated the role of motor set for location-dependent firing in freely moving rats and in restrained rats. After the implantation of electrodes in the CA1 region of hippocampus, neurons sensitive to the place and their activation fields were identified. At this point, animals were snugly wrapped in a towel fastened with clips, and consequently could not displace actively. In this condition, there was almost complete suppression of place selectivity in place cells’ activity. The authors concluded that motor set and, in particular, the preparedness to movement strongly contribute to the spatially selective activity of hippocampal place cells. In a similar vein, Gavrilov et al. (1998) investigated the role of location, movement and directional selectivity in rats that were passively displaced on a mobile robot. At variance with the previous study, in which the test in restrained condition was conducted only with previously identified place fields, in this case the robot (and the rat on it) followed standard trajectories starting from each corner of a square arena, thus covering an area much broader than the place field. O. Miglino M. Ponticorvo (&) Natural and Artificial Cognition Laboratory, Department of Relational Sciences, University of Naples ‘‘Federico II’’, Via Porta di Massa, 1, 80133 Naples, Italy e-mail: michela.ponticorvo@unina.it

Human breeders for evolving robots

In this article we describe a new approach in evolutionary robotics according to which human breeders are involved in the evolutionary process. While traditionally robots are selected to reproduce automatically according to a fitness formula, which is a quantitative and strictly defined measure, human breeders can operate selection based on qualitative criteria, and rewarding behaviors that can slip between the meshes woven by the fitness formula. In authors’ opinion this may bring advantages to the evolutionary robotics methodology, allowing the production of robots that display more, and more multiform, behaviors. In order to illustrate this approach, the software Breedbot was developed in which human breeders can intervene in evolving robots, complementing the automatic evaluation. After describing the software, some results on sample evolutionary processes are reported showing that the joint use of human and artificial selection on an exploration task generates robots with a higher performance and in a shorter time compared with the exclusive action of each breeding method. Future work will explore this hypothesis further.