http://popups.uliege.be/3041-539x/index.php?id=2859 Publications of Auteurs Kohei Nakajima fr 0 http://popups.uliege.be/3041-539x/index.php?id=4410 Our cognition is structuring the informational layer, consisting of perception, anticipation, and action, and it should also be sustained on a physical basis. In this paper, we aim to explore the relationship between the informational layer and the physical layer from a dynamical systems point of view. As an example, the fluctuation of choice is investigated by using a simulated agent. By setting a T-maze, the agent should choose one arm of the maze if a corresponding token is presented. We prepared two types of tokens, corresponding to the left and right arm of the maze. After training the network of the agent to successfully choose the corresponding arm, we presented two tokens simultaneously to the agent and observed its behavior. As a result, we found several behaviours, which are difficult to speculate on from a case in which only a single token is presented to the agent. Detailed analyses and the implications of the model are discussed. Thu, 10 Oct 2024 10:16:17 +0200 Thu, 10 Oct 2024 10:16:33 +0200 http://popups.uliege.be/3041-539x/index.php?id=4410 http://popups.uliege.be/3041-539x/index.php?id=3959 We address the excess entropy, which is a measure of complexity for stationary time series, from the ordinal point of view. We show that the permutation excess entropy is equal to the mutual information between two adjacent semi-infinite blocks in the space of orderings for finite-state stationary ergodic Markov processes. This result may spread a new light on the relationship between complexity and anticipation. Tue, 01 Oct 2024 16:48:42 +0200 Tue, 01 Oct 2024 16:50:15 +0200 http://popups.uliege.be/3041-539x/index.php?id=3959 http://popups.uliege.be/3041-539x/index.php?id=3023 In this paper, we propose a simple model that focuses on the adaptation process of an agent to an unknown system in an online manner. The agent is equipped with a recurrent neural network, and by controlling the dynamics of the interacting system, it should predict its state in one-step prediction. To quantitatively characterize the interaction modality between the agent and the interacting system, we used transfer entropy. As a result, by varying the nonlinear parameter of the interacting system and the coupling strength, we numerically show that the adaptation dynamics can be distinguished between an agent-driven and a non-agent-driven dynamics. Fri, 06 Sep 2024 16:02:20 +0200 Fri, 06 Sep 2024 16:02:28 +0200 http://popups.uliege.be/3041-539x/index.php?id=3023 http://popups.uliege.be/3041-539x/index.php?id=2857 Nonlinear dynamical systems show some different motions such as periodic, chaotic or intermittent ones. On-off intermittency is aperiodic switching motion between laminar phases and burst phases. It is observed in critical points with blowout bifurcation. Occurrence of it is sensitive with respect to parameter shifts in conventional systems. In the present paper, an extended dynamical system with an interaction between a global structure and a local motion is proposed. This interaction means a reciprocal definition between a parameter and state variables. The reciprocal definition is induced from the concept of a generative pointer that suggests an extended subobject classifier. Ubiquitous on-off intermittency is observed for a wide range of parameter values when a generative pointer is applied to a Henon map. This fact implies robustness of on-off intermittency against parameter shifts. Tue, 03 Sep 2024 15:24:24 +0200 Tue, 03 Sep 2024 15:24:31 +0200 http://popups.uliege.be/3041-539x/index.php?id=2857