Modelling of Multi-Agent Systems: Experiences with Membrane Computing and Future Challenges

Formal modelling of Multi-Agent Systems (MAS) is a challenging task due to high complexity, interaction, parallelism and continuous change of roles and organisation between agents. In this paper we record our research experience on formal modelling of MAS. We review our research throughout the last decade, by describing the problems we have encountered and the decisions we have made towards resolving them and providing solutions. Much of this work involved membrane computing and classes of P Systems, such as Tissue and Population P Systems, targeted to the modelling of MAS whose dynamic structure is a prominent characteristic. More particularly, social insects (such as colonies of ants, bees, etc.), biology inspired swarms and systems with emergent behaviour are indicative examples for which we developed formal MAS models. Here, we aim to review our work and disseminate our findings to fellow researchers who might face similar challenges and, furthermore, to discuss important issues for advancing research on the application of membrane computing in MAS modelling.Comment: In Proceedings AMCA-POP 2010, arXiv:1008.314

Simulating activities: Relating motives, deliberation, and attentive coordination

Activities are located behaviors, taking time, conceived as socially meaningful, and usually involving interaction with tools and the environment. In modeling human cognition as a form of problem solving (goal-directed search and operator sequencing), cognitive science researchers have not adequately studied “off-task” activities (e.g., waiting), non-intellectual motives (e.g., hunger), sustaining a goal state (e.g., playful interaction), and coupled perceptual-motor dynamics (e.g., following someone). These aspects of human behavior have been considered in bits and pieces in past research, identified as scripts, human factors, behavior settings, ensemble, flow experience, and situated action. More broadly, activity theory provides a comprehensive framework relating motives, goals, and operations. This paper ties these ideas together, using examples from work life in a Canadian High Arctic research station. The emphasis is on simulating human behavior as it naturally occurs, such that “working” is understood as an aspect of living. The result is a synthesis of previously unrelated analytic perspectives and a broader appreciation of the nature of human cognition. Simulating activities in this comprehensive way is useful for understanding work practice, promoting learning, and designing better tools, including human-robot systems

Engineering simulations for cancer systems biology

Computer simulation can be used to inform in vivo and in vitro experimentation, enabling rapid, low-cost hypothesis generation and directing experimental design in order to test those hypotheses. In this way, in silico models become a scientific instrument for investigation, and so should be developed to high standards, be carefully calibrated and their findings presented in such that they may be reproduced. Here, we outline a framework that supports developing simulations as scientific instruments, and we select cancer systems biology as an exemplar domain, with a particular focus on cellular signalling models. We consider the challenges of lack of data, incomplete knowledge and modelling in the context of a rapidly changing knowledge base. Our framework comprises a process to clearly separate scientific and engineering concerns in model and simulation development, and an argumentation approach to documenting models for rigorous way of recording assumptions and knowledge gaps. We propose interactive, dynamic visualisation tools to enable the biological community to interact with cellular signalling models directly for experimental design. There is a mismatch in scale between these cellular models and tissue structures that are affected by tumours, and bridging this gap requires substantial computational resource. We present concurrent programming as a technology to link scales without losing important details through model simplification. We discuss the value of combining this technology, interactive visualisation, argumentation and model separation to support development of multi-scale models that represent biologically plausible cells arranged in biologically plausible structures that model cell behaviour, interactions and response to therapeutic interventions

Cognitive modeling of social behaviors

To understand both individual cognition and collective activity, perhaps the greatest opportunity today is to integrate the cognitive modeling approach (which stresses how beliefs are formed and drive behavior) with social studies (which stress how relationships and informal practices drive behavior). The crucial insight is that norms are conceptualized in the individual mind as ways of carrying out activities. This requires for the psychologist a shift from only modeling goals and tasks —why people do what they do—to modeling behavioral patterns—what people do—as they are engaged in purposeful activities. Instead of a model that exclusively deduces actions from goals, behaviors are also, if not primarily, driven by broader patterns of chronological and located activities (akin to scripts). To illustrate these ideas, this article presents an extract from a Brahms simulation of the Flashline Mars Arctic Research Station (FMARS), in which a crew of six people are living and working for a week, physically simulating a Mars surface mission. The example focuses on the simulation of a planning meeting, showing how physiological constraints (e.g., hunger, fatigue), facilities (e.g., the habitat’s layout) and group decision making interact. Methods are described for constructing such a model of practice, from video and first-hand observation, and how this modeling approach changes how one relates goals, knowledge, and cognitive architecture. The resulting simulation model is a powerful complement to task analysis and knowledge-based simulations of reasoning, with many practical applications for work system design, operations management, and training

Telerobotic workstation design aid

Telerobot systems are being developed to support a number of space mission applications. In low earth orbit, telerobots and teleoperated manipulators will be used in shuttle operations and space station construction/maintenance. Free flying telerobotic service vehicles will be used at low and geosynchronous orbital operations. Rovers and autonomous vehicles will be equipped with telerobotic devices in planetary exploration. In all of these systems, human operators will interact with the robot system at varied levels during the scheduled operations. The human operators may be in either orbital or ground-based control systems. To assure integrated system development and maximum utility across these systems, designers must be sensitive to the constraints and capabilities that the human brings to system operation and must be assisted in applying these human factors to system development. The simulation and analysis system is intended to serve the needs of system analysis/designers as an integrated workstation in support of telerobotic design

Development of limiting dilution viability pcr method to assess the effectiveness of selected biocides to treat indoor fungi growth

Indoor fungal contamination should be treated with cost-effective and green methods. Biocides have direct biological effect on living organisms but the evidence on their control of indoor fungal contamination is scarce. Using conventional cultivation to evaluate their effectiveness is time consuming while polymerase chain reaction (PCR) provides a fast and reliable alternative. The incorporation of serial dilution technique and viability information in PCR has made it suitable to evaluate the effectiveness of biocides. Thus, this study aimed to assess the antifungal ability of biocides, zinc salicylate (ZS), calcium benzoate (CB) and potassium sorbate (KS) to treat indoor fungal contamination through developing limiting dilution viability PCR (vPCR). These biocides were selected as they successfully controlled the growth of indoor waterborne fungi previously. Indoor air sampling revealed that higher educational building of computer studies (Building A) and of civil engineering studies (Building B) were contaminated by 509 CFU/m3 and 805.7 CFU/m3 of indoor airborne fungi, respectively. Two indoor fungi, Talaromyces spp. and Aspergillus niger were identified. They were subjected to biocides-treatment and subsequent conventional cultivation and limiting dilution vPCR due to their potential risks against humans’ health. The limiting dilution vPCR was developed by incorporating the pre-treatment of propidium monoazide (PMA) before deoxyribonucleic acid (DNA) extraction and the serial dilution of the DNA template in PCR. This approach was proven to effectively enumerate the effectiveness of biocides to treat indoor fungi. KS was shown to have the best effectiveness (100%) to prevent the growth of Talaromyces spp, followed by ZS (80.8%) and CB (no effect). KS also showed the best effectiveness against A. niger (100%) at the early stage of the study but its effect reduced with time. ZS showed durable effect (66.67%) against A. niger Day 9 cultures. Inconstant results were indicated by cultivation method. This study has provided a cheaper, more accurate and suitable approach to determine the effectiveness of treatment of indoor fungi than cultivation methods

A Self-Organizing Neural Model of Motor Equivalent Reaching and Tool Use by a Multijoint Arm

This paper describes a self-organizing neural model for eye-hand coordination. Called the DIRECT model, it embodies a solution of the classical motor equivalence problem. Motor equivalence computations allow humans and other animals to flexibly employ an arm with more degrees of freedom than the space in which it moves to carry out spatially defined tasks under conditions that may require novel joint configurations. During a motor babbling phase, the model endogenously generates movement commands that activate the correlated visual, spatial, and motor information that are used to learn its internal coordinate transformations. After learning occurs, the model is capable of controlling reaching movements of the arm to prescribed spatial targets using many different combinations of joints. When allowed visual feedback, the model can automatically perform, without additional learning, reaches with tools of variable lengths, with clamped joints, with distortions of visual input by a prism, and with unexpected perturbations. These compensatory computations occur within a single accurate reaching movement. No corrective movements are needed. Blind reaches using internal feedback have also been simulated. The model achieves its competence by transforming visual information about target position and end effector position in 3-D space into a body-centered spatial representation of the direction in 3-D space that the end effector must move to contact the target. The spatial direction vector is adaptively transformed into a motor direction vector, which represents the joint rotations that move the end effector in the desired spatial direction from the present arm configuration. Properties of the model are compared with psychophysical data on human reaching movements, neurophysiological data on the tuning curves of neurons in the monkey motor cortex, and alternative models of movement control.National Science Foundation (IRI 90-24877); Office of Naval Research (N00014-92-J-1309); Air Force Office of Scientific Research (F49620-92-J-0499); National Science Foundation (IRI 90-24877

Application of palm shell activated carbon filter as a medium of indoor air contaminant adsorbent for indoor air quality improvement

For decades, the inclusion of activated carbon (AC) adsorption technique through filtration has gained significant interest on improvement of indoor air quality (IAQ) by reducing level of pollutant. The interest of reseachers in palm shell AC (PSAC) keep increase owing to the fact that this material has superior characteristic as compared to commercial AC. However, the investigation of PSAC performance for air filtration are still limited and no research could be found on relating the effect of burner for carbonization on PSAC properties. Therefore, the current research was focused on producing PSAC by using new fabricated burner, exploring the effect of combination of physical and chemical activation towards PSAC properties and investigating of PSAC air filter performance used in Mechanical Ventilation Air Conditioning (MVAC) system. Preliminary studies began with IAQ monitoring in different building condition. The present data revealed that at certain situation, the buildings environment was below than satisfactory level and required mitigation plan by introducing new air filtration media in MVAC system. The best quality of charcoal was obtained by Horizontal burner with less fume formation during carbonization process compare to other design. The physical properties analysis of palm shell charcoal showed the carbonization time (CT) 2 hours gained better charcoal properties and highly recommended to continue into the activation process. After the activation process, PSAC physical+chemical shows significantly higher pore development, surface area and adsorption capacity compare to the other process. The lowest density and the highest porosity up to 0.4632 g/cm and 7.11% was calculated while the highest Iodine number of 1091.05 mg/g and BET surface area of 713.7 m 3 /g was obtained respectively in PSAC physical+chemical. Meanwhile, microstructure and composition analysis shows that, PSAC physical+chemical fully produced honeycomb form of porosity and comprised of C, O, K and Ca contents for high adsorption capacity. The improvement of IAQ in the buildings was achieved with the application of PSAC air filter which shows low concentration of CO2 with 302 ppm, CO with 0.4 ppm , TVOC with 0.1 ppm and PM10 with 0.02mg/m 2 respectively compare to the commercial filter

Apperceptive patterning: Artefaction, extensional beliefs and cognitive scaffolding

In “Psychopower and Ordinary Madness” my ambition, as it relates to Bernard Stiegler’s recent literature, was twofold: 1) critiquing Stiegler’s work on exosomatization and artefactual posthumanism—or, more specifically, nonhumanism—to problematize approaches to media archaeology that rely upon technical exteriorization; 2) challenging how Stiegler engages with Giuseppe Longo and Francis Bailly’s conception of negative entropy. These efforts were directed by a prevalent techno-cultural qualifier: the rise of Synthetic Intelligence (including neural nets, deep learning, predictive processing and Bayesian models of cognition). This paper continues this project but first directs a critical analytic lens at the Derridean practice of the ontologization of grammatization from which Stiegler emerges while also distinguishing how metalanguages operate in relation to object-oriented environmental interaction by way of inferentialism. Stalking continental (Kapp, Simondon, Leroi-Gourhan, etc.) and analytic traditions (e.g., Carnap, Chalmers, Clark, Sutton, Novaes, etc.), we move from artefacts to AI and Predictive Processing so as to link theories related to technicity with philosophy of mind. Simultaneously drawing forth Robert Brandom’s conceptualization of the roles that commitments play in retrospectively reconstructing the social experiences that lead to our endorsement(s) of norms, we compliment this account with Reza Negarestani’s deprivatized account of intelligence while analyzing the equipollent role between language and media (both digital and analog)