<> "The repository administrator has not yet configured an RDF license."^^ . <> . . "Cognition as management of meaningful information. Proposal for an evolutionary approach. "^^ . "Humans are cognitive entities. Our behaviors and ongoing interactions with the environment are\r\nthreaded with creations and usages of meaningful information, be they conscious or unconscious.\r\nAnimal life is also populated with meaningful information related to the survival of the individual\r\nand of the species. The meaningfulness of information managed by artificial agents can also be\r\nconsidered as a reality once we accept that the meanings managed by an artificial agent are\r\nderived from what we, the cognitive designers, have built the agent for.\r\nThis rapid overview brings to consider that cognition, in terms of management of meaningful\r\ninformation, can be looked at as a reality for animal, humans and robots. But it is pretty clear\r\nthat the corresponding meanings will be very different in nature and content. Free will and selfconsciousness\r\nare key drivers in the management of human meanings, but they do not exist for\r\nanimals or robots. Also, staying alive is a constraint that we share with animals. Robots do not\r\ncarry that constraint.\r\nSuch differences in meaningful information and cognition for animal, humans and robots could\r\nbring us to believe that the analysis of cognitions for these three types of agents has to be done\r\nseparately. But if we agree that humans are the result of the evolution of life and that robots are a\r\nproduct of human activities, we can then look at addressing the possibility for an evolutionary\r\napproach at cognition based on meaningful information management. A bottom-up path would\r\nbegin by meaning management within basic living entities, then climb up the ladder of evolution\r\nup to us humans, and continue with artificial agents.\r\nThis is what we propose to present here: address an evolutionary approach for cognition, based\r\non meaning management using a simple systemic tool.\r\nWe use for that an existing systemic approach on meaning generation where a system submitted\r\nto a constraint generates a meaningful information (a meaning) that will initiate an action in order\r\nto satisfy the constraint [1,2]. The action can be physical, mental or other.\r\nThis systemic approach defines a Meaning Generator System (MGS). The simplicity of the MGS\r\nmakes it available as a building block for meaning management in animals, humans and robots.\r\nContrary to approaches on meaning generation in psychology or linguistics, the MGS approach is\r\nnot based on human mind. To avoid circularity, an evolutionary approach has to be careful not to\r\ninclude components of human mind in the starting point.\r\nThe MGS receives information from its environment and compares it with its constraint. The\r\ngenerated meaning is the connection existing between the received information and the\r\nconstraint. The generated meaning is to trigger an action aimed at satisfying the constraint. The\r\naction will modify the environment, and so the generated meaning. Meaning generation links\r\nagents to their environments in a dynamic mode. The MGS approach is triadic, Peircean type.\r\nThe systemic approach allows wide usage of the MGS: a system is a set of elements linked by a\r\nset of relations. Any system submitted to a constraint and capable of receiving information from\r\nits environment can lead to a MGS. Meaning generation can be applied to many cases, assuming\r\nwe identify clearly enough the systems and the constraints. Animals, humans and robots are then\r\nagents containing MGSs. Similar MGSs carrying different constraints will generate different\r\nmeanings. Cognition is system dependent.\r\nWe first apply the MGS approach to animals with “stay alive” and “group life” constraints. Such\r\nconstraints can bring to model many cases of meaning generation and actions in the organic\r\nworld. However, it is to be highlighted that even if the functions and characteristics of life are well\r\nknown, the nature of life is not really understood. Final causes are difficult to integrate in our\r\ntoday science. So analyzing meaning and cognition in living entities will have to take into account\r\nour limited understanding about the nature of life. Ongoing research on concepts like autopoiesis\r\ncould bring a better understanding about the nature of life [3].\r\nWe next address meaning generation for humans. The case is the most difficult as the nature of\r\nhuman mind is a mystery for today science and philosophy. The natures of our feelings, free will\r\nor self-consciousness are unknown. Human constraints, meanings and cognition are difficult to\r\ndefine. Any usage of the MGS approach for humans will have to take into account the limitations\r\nthat result from the unknown nature of human mind.\r\nWe will however present some possible approaches to identify human constraints where the MGS\r\nbrings some openings in an evolutionary approach [4, 5]. But it is clear that the better human\r\nmind will be understood, the more we will be in a position to address meaning management and\r\ncognition for humans. Ongoing research activities relative to the nature of human mind cover\r\nmany scientific and philosophical domains [6].\r\nThe case of meaning management and cognition in artificial agents is rather straightforward with\r\nthe MGS approach as we, the designers, know the agents and the constraints. In addition, our\r\nevolutionary approach brings to position notions like artificial constraints, meaning and autonomy\r\nas derived from their animal or human source.\r\nWe next highlight that cognition as management of meaningful information by agents goes\r\nbeyond information and needs to address representations which belong to the central hypothesis\r\nof cognitive sciences.\r\nWe define the meaningful representation of an item for an agent as being the networks of\r\nmeanings relative to the item for the agent, with the action scenarios involving the item.\r\nSuch meaningful representations embed the agents in their environments and are far from the\r\nGOFAI type ones [4]. Meanings, representations and cognition exist by and for the agents.\r\nWe finish by summarizing the points presented and highlight some possible continuations.\r\n[1] C. Menant \"Information and Meaning\" http://cogprints.org/3694/\r\n[2] C. Menant “Introduction to a Systemic Theory of Meaning” (short paper)\r\nhttp://crmenant.free.fr/ResUK/MGS.pdf\r\n[3] A. Weber and F. Varela “Life after Kant: Natural purposes and the autopoietic foundations of\r\nbiological individuality”. Phenomenology and the Cognitive Sciences 1: 97–125, 2002.\r\n[4] C. Menant \"Computation on Information, Meaning and Representations. An Evolutionary\r\nApproach\" http://www.idt.mdh.se/ECAP-2005/INFOCOMPBOOK/CHAPTERS/10-Menant.pdf\r\nhttp://crmenant.free.fr/2009BookChapter/C.Menant.211009\r\n[5] C. Menant \"Proposal for a shared evolutionary nature of language and consciousness\"\r\nhttp://cogprints.org/7067/\r\n[6] Philpapers “philosophy of mind” http://philpapers.org/browse/philosophy-of-mind"^^ . "2011-07" . . . . . . . . . "Christophe"^^ . "Menant"^^ . "Christophe Menant"^^ . . . . . . "Cognition as management of meaningful information. Proposal for an evolutionary approach. (Other)"^^ . . . . . . . . . "C.Menant-Presentation.pdf"^^ . . . "Cognition as management of meaningful information. Proposal for an evolutionary approach. (Image (JPEG))"^^ . . . . . . "preview.jpg"^^ . . . "Cognition as management of meaningful information. Proposal for an evolutionary approach. (Indexer Terms)"^^ . . . . . . "indexcodes.txt"^^ . . . "Cognition as management of meaningful information. Proposal for an evolutionary approach. (PDF)"^^ . . . . . . . . . "C.Menant-IACAP2011-Presentation.pdf"^^ . . . "Cognition as management of meaningful information. Proposal for an evolutionary approach. (Image (JPEG))"^^ . . . . . . "preview.jpg"^^ . . . "Cognition as management of meaningful information. Proposal for an evolutionary approach. (Indexer Terms)"^^ . . . . . . "indexcodes.txt"^^ . . "HTML Summary of #7584 \n\nCognition as management of meaningful information. Proposal for an evolutionary approach. \n\n" . "text/html" . . . "Animal Cognition" . . . "Evolution" . . . "Primatology" . . . "Artificial Intelligence" . . . "Evolutionary Psychology" . . . "Epistemology" . . . "Philosophy of Mind" . .