Fuzzy Bigraphs: An Exercise in Fuzzy Communicating Agents

Bigraphs and their algebra is a model of concurrency. Fuzzy bigraphs are a generalization of birgraphs intended to be a model of concurrency that incorporates vagueness. More specifically, this model assumes that agents are similar, communication is not perfect, and, in general, everything is or happens to some degree.Comment: 11 pages, 3 figure

A Congruence for Petri Nets

We introduce a way of viewing Petri nets as open systems. This is done by considering a bicategory of cospans over a category of p/t nets and embeddings. We derive a labelled transition system (LTS) semantics for such nets using GIPOs and characterise the resulting congruence. Technically, our results are similar to the recent work by Milner on applying the theory of bigraphs to Petri Nets. The two main differences are that we treat p/t nets instead of c/e nets and we deal directly with a category of nets instead of encoding them into bigraphs

A Geometric Approach to the Problem of Unique Decomposition of Processes

This paper proposes a geometric solution to the problem of prime decomposability of concurrent processes first explored by R. Milner and F. Moller in [MM93]. Concurrent programs are given a geometric semantics using cubical areas, for which a unique factorization theorem is proved. An effective factorization method which is correct and complete with respect to the geometric semantics is derived from the factorization theorem. This algorithm is implemented in the static analyzer ALCOOL.Comment: 15 page

Sequentiality vs. Concurrency in Games and Logic

Connections between the sequentiality/concurrency distinction and the semantics of proofs are investigated, with particular reference to games and Linear Logic.Comment: 35 pages, appeared in Mathematical Structures in Computer Scienc

Know-how, intellectualism, and memory systems

ABSTRACTA longstanding tradition in philosophy distinguishes between knowthatand know-how. This traditional “anti-intellectualist” view is soentrenched in folk psychology that it is often invoked in supportof an allegedly equivalent distinction between explicit and implicitmemory, derived from the so-called “standard model of memory.”In the last two decades, the received philosophical view has beenchallenged by an “intellectualist” view of know-how. Surprisingly, defenders of the anti-intellectualist view have turned to the cognitivescience of memory, and to the standard model in particular, todefend their view. Here, I argue that this strategy is a mistake. As it turns out, upon closer scrutiny, the evidence from cognitivepsychology and neuroscience of memory does not support theanti-intellectualist approach, mainly because the standard modelof memory is likely wrong. However, this need not be interpretedas good news for the intellectualist, for it is not clear that theempirical evidence necessarily supp..

Towards a Formal Framework for Mobile, Service-Oriented Sensor-Actuator Networks

Service-oriented sensor-actuator networks (SOSANETs) are deployed in health-critical applications like patient monitoring and have to fulfill strong safety requirements. However, a framework for the rigorous formal modeling and analysis of SOSANETs does not exist. In particular, there is currently no support for the verification of correct network behavior after node failure or loss/addition of communication links. To overcome this problem, we propose a formal framework for SOSANETs. The main idea is to base our framework on the \pi-calculus, a formally defined, compositional and well-established formalism. We choose KLAIM, an existing formal language based on the \pi-calculus as the foundation for our framework. With that, we are able to formally model SOSANETs with possible topology changes and network failures. This provides the basis for our future work on prediction, analysis and verification of the network behavior of these systems. Furthermore, we illustrate the real-life applicability of this approach by modeling and extending a use case scenario from the medical domain.Comment: In Proceedings FESCA 2013, arXiv:1302.478

Decoding information in the human hippocampus: a user's guide

Multi-voxel pattern analysis (MVPA), or 'decoding', of fMRI activity has gained popularity in the neuroimaging community in recent years. MVPA differs from standard fMRI analyses by focusing on whether information relating to specific stimuli is encoded in patterns of activity across multiple voxels. If a stimulus can be predicted, or decoded, solely from the pattern of fMRI activity, it must mean there is information about that stimulus represented in the brain region where the pattern across voxels was identified. This ability to examine the representation of information relating to specific stimuli (e.g., memories) in particular brain areas makes MVPA an especially suitable method for investigating memory representations in brain structures such as the hippocampus. This approach could open up new opportunities to examine hippocampal representations in terms of their content, and how they might change over time, with aging, and pathology. Here we consider published MVPA studies that specifically focused on the hippocampus, and use them to illustrate the kinds of novel questions that can be addressed using MVPA. We then discuss some of the conceptual and methodological challenges that can arise when implementing MVPA in this context. Overall, we hope to highlight the potential utility of MVPA, when appropriately deployed, and provide some initial guidance to those considering MVPA as a means to investigate the hippocampus