Exploiting Environmental Computation in a Multi-Agent Model of Slime Mould

Very simple organisms, such as the single-celled amoeboid slime mould Physarum polycephalum possess no neural tissue yet, despite this, are known to exhibit complex biological and computational behaviour. Given such limited resources, can environmental stimuli play a role in generating the complexity of slime mould behaviour? We use a multi-agent collective model of slime mould to explore a two-way mechanism where the collective behaviour is influenced by simulated chemical concentration gradient fields and, in turn, this behaviour alters the spatial pattern of the concentration gradients. This simple mechanism yields complex behaviour amid the dynamically changing gradient profiles and suggests how the apparently intelligent response of the slime mould could possibly be due to outsourcing of computation to the environment.Comment: 2014 ABBII International Symposium on Artificial, Biological and Bio-Inspired Intelligence, 27-28th September, Rhodes, Greec

Towards Physarum Binary Adders

Plasmodium of \emph{Physarum polycephalum} is a single cell visible by unaided eye. The plasmodium's foraging behaviour is interpreted in terms of computation. Input data is a configuration of nutrients, result of computation is a network of plasmodium's cytoplasmic tubes spanning sources of nutrients. Tsuda et al (2004) experimentally demonstrated that basic logical gates can be implemented in foraging behaviour of the plasmodium. We simplify the original designs of the gates and show --- in computer models --- that the plasmodium is capable for computation of two-input two-output gate $\to$ and three-input two-output $\to$. We assemble the gates in a binary one-bit adder and demonstrate validity of the design using computer simulation.Comment: Biosystems (2010), in press. Please download final version of the paper from the Publishers's sit

Road planning with slime mould: If Physarum built motorways it would route M6/M74 through Newcastle

Plasmodium of Physarum polycephalum is a single cell visible by unaided eye. During its foraging behaviour the cell spans spatially distributed sources of nutrients with a protoplasmic network. Geometrical structure of the protoplasmic networks allows the plasmodium to optimize transfer of nutrients between remote parts of its body, to distributively sense its environment, and make a decentralized decision about further routes of migration. We consider the ten most populated urban areas in United Kingdom and study what would be an optimal layout of transport links between these urban areas from the "plasmodium's point of view". We represent geographical locations of urban areas by oat flakes, inoculate the plasmodium in Greater London area and analyse the plasmodium's foraging behaviour. We simulate the behaviour of the plasmodium using a particle collective which responds to the environmental conditions to construct and minimise transport networks. Results of our scoping experiments show that during its colonization of the experimental space the plasmodium forms a protoplasmic network isomorphic to a network of major motorways except the motorway linking England with Scotland. We also imitate the reaction of transport network to disastrous events and show how the transport network can be reconfigured during natural or artificial cataclysms. The results of the present research lay a basis for future science of bio-inspired urban and road planning.Comment: Submitted November (2009

Gauge Coupling Unification in MSSM + 5 Flavors

We investigate gauge coupling unification at 2-loops for theories with 5 extra vectorlike SU(5) fundamentals added to the MSSM. This is a borderline case where unification is only predicted in certain regions of parameter space. We establish a lower bound on the scale for the masses of the extra flavors, as a function of the sparticle masses. Models far outside of the bound do not predict unification at all (but may be compatible with unification), and models outside but near the boundary cannot reliably claim to predict it with an accuracy comparable to the MSSM prediction. Models inside the boundary can work just as well as the MSSM.Comment: 28 pages, 13 figures. Added references, fixed minor typos. No changes to content. Page count was incorrect in v1 Comment