A BDI agent architecture for the GAMA modeling and simulation platform

International audienceWith the increase of computing power and the development of user-friendly multi-agent simulation frameworks, social simulations have become increasingly realistic. However, most agent architectures in these simulations use simple reactive models. Indeed, cognitive agent architectures face two main obstacles: their complexity for the field-expert modeler, and their computational cost. In this paper, we propose a new cognitive agent architecture based on the BDI (Belief-Desire-Intention) paradigm integrated into the GAMA modeling platform and its GAML modeling language. This architecture was designed to be simple-to-use for modelers, flexible enough to manage complex behaviors, and with low computational cost. An experiment carried out with different profiles of end-users shows that the architecture is actually usable even by modelers who have little knowledge in programming and in Artificial Intelligence

Refounding of Activity Concept ? Towards a Federative Paradigm for Modeling and Simulation

Journal : Simulation, Transactions of the Society for Modeling and Simulation InternationalInternational audienceCurrently, the widely used notion of activity is increasingly present in computer science. However, because this notion is used in specific contexts, it becomes vague. Here, the notion of activity is scrutinized in various contexts and, accord-ingly, put in perspective. It is discussed through four scientific disciplines: computer science, biology, economics, and epis-temology. The definition of activity usually used in simulation is extended to new qualitative and quantitative definitions. In computer science, biology and economics disciplines, the new simulation activity definition is first applied critically. Then, activity is discussed generally. In epistemology, activity is discussed, in a prospective way, as a possible framework in models of human beliefs and knowledge

Induction of Sodium/Iodide Symporter (NIS) Expression and Radioiodine Uptake in Non-Thyroid Cancer Cells

Background: This study was designed to explore the therapeutic potential of suppressing MAP kinase and PI3K/Akt pathways and histone deacetylase (HDAC) to induce the expression of sodium/iodide symporter (NIS) and radioiodine uptake in non-thyroid cancer cells. Methods: We tested the effects of the MEK inhibitor RDEA119, the Akt inhibitor perifosine, and the HDAC inhibitor SAHA on NIS expression in thirteen human cancer cell lines derived from melanoma, hepatic carcinoma, gastric carcinoma, colon carcinoma, breast carcinoma, and brain cancers. We also examined radioiodine uptake and histone acetylation at the NIS promoter in selected cells. Results: Overall, the three inhibitors could induce NIS expression, to various extents, in melanoma and all the epithelial carcinoma-derived cells but not in brain cancer-derived cells. SAHA was most effective and its effect could be significantly enhanced by RDEA119 and perifosine. The expression of NIS, at both mRNA and protein levels, was most robust in the melanoma cell M14, hepatic carcinoma cell HepG2, and the gastric carcinoma cell MKN-7 cell. Radioiodine uptake was correspondingly induced, accompanied by robust increase in histone acetylation at the NIS promoter, in these cells when treated with the three inhibitors. Conclusions: This is the first demonstration that simultaneously suppressing the MAP kinase and PI3K/Akt pathways and HDAC could induce robust NIS expression and radioiodine uptake in certain non-thyroid human cancer cells, providing novel therapeutic implications for adjunct radioiodine treatment of these cancers

Search for NTRK1 proto-oncogene rearrangements in human thyroid tumours originated after therapeutic radiation

Rearrangements of NTRK1 proto-oncogene were detected in ‘spontaneous’ papillary thyroid carcinomas with a frequency varying from 5 to 25% in different studies. These rearrangements result in the formation of chimaeric genes composed of the tyrosine kinase domain of NTRK1 fused to 5′ sequences of different genes. To investigate if the NTRK1 gene plays a role in radiation-induced thyroid carcinogenesis, we looked for the presence of NTRK1 -activating rearrangements in 32 human thyroid tumours (16 follicular adenomas, 14 papillary carcinomas and two lymph-node metastases of papillary thyroid carcinomas) from patients who had received external radiation, using the reverse transcription polymerase chain reaction, Southern blot and direct sequencing techniques. These data were compared with those obtained in a series of 28 ‘spontaneous’ benign and malignant thyroid tumours, collected from patients without a history of radiation exposure and four in vitro culture cell lines derived from ‘spontaneous’ thyroid cancers. Our results concerning the radiation-associated tumours showed that only rearrangements between NTRK1 and TPM3 genes (TRK oncogene) were detected in 2/14 papillary carcinomas and in one lymph-node metastasis of one of these papillary thyroid carcinomas. All the radiation-associated adenomas were negative. In the ‘spontaneous’ tumours, only one of the 14 papillary carcinomas and one of the four in vitro culture cell lines, derived from a papillary carcinoma, presented a NTRK1 rearrangement also with the TPM3 gene. Twenty-five of this series of radiation-associated tumours were previously studied for the ras and RET/PTC oncogenes. In conclusion, our data: (a) show that the overall frequency of NTRK1 rearrangements is similar between radiation-associated (2/31: 6%) and ‘spontaneous’ epithelial thyroid tumours (2/32: 6%). The frequency, if we consider exclusively the papillary carcinomas, is in both cases 12%; (b) show that the TRK oncogene plays a role in the development of a minority of radiation-associated papillary thyroid carcinomas but not in adenomas; and (c) confirm that RET/PTC rearrangements are the major genetic alteration associated with ionizing radiation-induced thyroid tumorigenesis. © 2000 Cancer Research Campaig

Agent-based spatial simulation with NetLogo : volume 1 : introduction and bases

The previous chapters have allowed us to introduce the basics of agent-based model creation with NetLogo. This has resulted in a model such as the one used in our running example. Once the model has been built, the aim is to manipulate it in such a way that new knowledge about the modeled phenomenon can be created. For example, we could look to study the rate of infection resulting from certain parameter values. The use and study of a model is nonetheless as complex as its creation. As such, using our model, we could launch the simulation with standard initial parameters (say 300 humans, 500 mosquitoes, a contamination distance of 5 and a work-home distance of 500), and we would obtain the graph indicating no infection beyond the source mosquito, which would lead us to conclude that these parameters lead to no infections. However, upon relaunching the simulation with the exact same values, we might obtain the graph with the infection present in almost 100% of individuals after 1000 iterations