71,187 research outputs found
How to Knit Your Own Markov Blanket
Hohwy (Hohwy 2016, Hohwy 2017) argues there is a tension between the free energy principle and leading depictions of mind as embodied, enactive, and extended (so-called âEEE1 cognitionâ). The tension is traced to the importance, in free energy formulations, of a conception of mind and agency that depends upon the presence of a âMarkov blanketâ demarcating the agent from the surrounding world. In what follows I show that the Markov blanket considerations do not, in fact, lead to the kinds of tension that Hohwy depicts. On the contrary, they actively favour the EEE story. This is because the Markov property, as exemplified in biological agents, picks out neither a unique nor a stationary boundary. It is this multiplicity and mutabilityâ rather than the absence of agent-environment boundaries as such - that EEE cognition celebrates
The relation between language and theory of mind in development and evolution
Considering the close relation between language and theory of mind in development and their tight connection in social behavior, it is no big leap to claim that the two capacities have been related in evolution as well. But what is the exact relation between them? This paper attempts to clear a path toward an answer. I consider several possible relations between the two faculties, bring conceptual arguments and empirical evidence to bear on them, and end up arguing for a version of co-evolution. To model this co-evolution, we must distinguish between different stages or levels of language and theory of mind, which fueled each otherâs evolution in a protracted escalation process
The diplomat's dilemma: Maximal power for minimal effort in social networks
Closeness is a global measure of centrality in networks, and a proxy for how
influential actors are in social networks. In most network models, and many
empirical networks, closeness is strongly correlated with degree. However, in
social networks there is a cost of maintaining social ties. This leads to a
situation (that can occur in the professional social networks of executives,
lobbyists, diplomats and so on) where agents have the conflicting objectives of
aiming for centrality while simultaneously keeping the degree low. We
investigate this situation in an adaptive network-evolution model where agents
optimize their positions in the network following individual strategies, and
using only local information. The strategies are also optimized, based on the
success of the agent and its neighbors. We measure and describe the time
evolution of the network and the agents' strategies.Comment: Submitted to Adaptive Networks: Theory, Models and Applications, to
be published from Springe
Adaptive Expectations, Confirmatory Bias, and Informational Efficiency
We study the informational efficiency of a market with a single traded asset.
The price initially differs from the fundamental value, about which the agents
have noisy private information (which is, on average, correct). A fraction of
traders revise their price expectations in each period. The price at which the
asset is traded is public information. The agents' expectations have an
adaptive component and a social-interactions component with confirmatory bias.
We show that, taken separately, each of the deviations from rationality worsen
the information efficiency of the market. However, when the two biases are
combined, the degree of informational inefficiency of the market (measured as
the deviation of the long-run market price from the fundamental value of the
asset) can be non-monotonic both in the weight of the adaptive component and in
the degree of the confirmatory bias. For some ranges of parameters, two biases
tend to mitigate each other's effect, thus increasing the informational
efficiency
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