by Keyword: Mind

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Biosca, A., Cabanach, P., Abdulkarim, M., Gumbleton, M., Gómez-Canela, C., Ramírez, M., Bouzón-Arnáiz, I., Avalos-Padilla, Y., Borros, S., Fernàndez-Busquets, X., (2021). Zwitterionic self-assembled nanoparticles as carriers for Plasmodium targeting in malaria oral treatment Journal of Controlled Release 331, 364-375

The current decline in antimalarial drug efficacy due to the evolution of resistant Plasmodium strains calls for new strategies capable of improving the bioavailability of antimalarials, especially of those whose lipophilic character imparts them a low solubility in biological fluids. Here we have designed, synthesized and characterized amphiphilic zwitterionic block copolymers forming nanoparticles capable of penetrating the intestinal epithelium that can be used for oral administration. Poly(butyl methacrylate-co-morpholinoethyl sulfobetaine methacrylate) (PBMA-MESBMA)-based nanoparticles exhibited a specific targeting to Plasmodium falciparum-infected vs. parasite-free red blood cells (74.8%/0.8% respectively), which was maintained upon encapsulation of the lipophilic antimalarial drug curcumin (82.6%/0.3%). The in vitro efficacy of curcumin upon encapsulation was maintained relative to the free compound, with an IC50 around 5 μM. In vivo assays indicated a significantly increased curcumin concentration in the blood of mice one hour after being orally fed PBMA-MESBMA-curcumin in comparison to the administration of free drug (18.7 vs. 2.1 ng/ml, respectively). At longer times, however, plasma curcumin concentration equaled between free and encapsulated drug, which was reflected in similar in vivo antimalarial activities in Plasmodium yoelii yoelii-infected mice. Microscopic analysis in blood samples of fluorescently labeled PBMA-MESBMA revealed the presence of the polymer inside P. yoelii yoelii-parasitized erythrocytes one hour after oral administration to infected animals. © 2021 Elsevier B.V.

Keywords: Curcumin, Drug delivery, Malaria, PBMA-MESBMA, Plasmodium, Zwitterionic block copolymers

Arsiwalla, X. D., Freire, I. T., Vouloutsi, V., Verschure, P., (2019). Latent morality in algorithms and machines Biomimetic and Biohybrid Systems 8th International Conference, Living Machines 2019 (Lecture Notes in Computer Science) , Springer, Cham (Nara, Japan) 11556, 309-315

Can machines be endowed with morality? We argue that morality in the descriptive or epistemic sense can be extended to artificial systems. Following arguments from evolutionary game-theory, we identify two main ingredients required to operationalize this notion of morality in machines. The first, being a group theory of mind, and the second, being an assignment of valence. We make the case for the plausibility of these operations in machines without reference to any form of intentionality or consciousness. The only systems requirements needed to support the above two operations are autonomous goal-directed action and the ability to interact and learn from the environment. Following this we have outlined a theoretical framework based on conceptual spaces and valence assignments to gauge latent morality in autonomous machines and algorithms.

Keywords: Autonomous systems, Ethics of algorithms, Goal-directed action, Philosophy of morality, Qualia, Theory of mind

Verschure, P., (2018). The architecture of mind and brain Living machines: A handbook of research in biomimetics and biohybrid systems (ed. Prescott, T. J., Lepora, Nathan, Verschure, P.), Oxford Scholarship (Oxford, UK) , 338-345

The components of a Living Machine must be integrated into a functioning whole, which requires a detailed understanding of the architecture of living machines. This chapter starts with a conceptual and historical analysis which from Plato brings us to nineteenth-century neuroscience and early concepts of the layered structure of nervous systems. These concepts were further captured in the cognitive behaviorism of Tolman and came to full fruition in the cognitive revolution of the second half of the twentieth century. Verschure subsequently describes the most relevant proposals of cognitive architectures followed by an overview of the few proposals stemming from modern neuroscience on the architecture of the brain. Subsequently, we will look at contemporary contenders that mediate between cognitive and brain architecture. An important challenge to any model of cognitive architectures is how to benchmark it. Verschure proposes the Unified Theories of Embodied Minds (UTEM) benchmark which advances from Newell’s classic Unified Theories of Cognition benchmark.

Keywords: Architecture, Mind, Brain, Organization, System, Virtualization, Abstraction layers

Freire, I. T., Arsiwalla, X. D., Puigbò, J. Y., Verschure, P., (2018). Limits of multi-agent predictive models in the formation of social conventions Frontiers in Artificial Intelligence and Applications (ed. Falomir, Z., Gibert, K., Plaza, E.), IOS Press (Amsterdam, The Netherlands) Volume 308: Artificial Intelligence Research and Development, 297-301

A major challenge in cognitive science and AI is to understand how intelligent agents might be able to predict mental states of other agents during complex social interactions. What are the computational principles of such a Theory of Mind (ToM)? In previous work, we have investigated hypotheses of how the human brain might realize a ToM of other agents in a multi-agent social scenario. In particular, we have proposed control-based cognitive architectures to predict the model of other agents in a game-theoretic task (Battle of the Exes). Our multi-layer architecture implements top-down predictions from adaptive to reactive layers of control and bottom-up error feedback from reactive to adaptive layers. We tested cooperative and competitive strategies among different multi-agent models, demonstrating that while pure RL leads to reasonable efficiency and fairness in social interactions, there are other architectures that can perform better in specific circumstances. However, we found that even the best predictive models fall short of human data in terms of stability of social convention formation. In order to explain this gap between humans and predictive AI agents, in this work we propose introducing the notion of trust in the form of mutual agreements between agents that might enhance stability in the formation of conventions such as turn-taking.

Keywords: Cognitive Architectures, Game Theory, Multi-Agent Models, Reinforcement Learning, Theory of Mind