Deep neural networks (DNNs) have had extraordinary successes in classifying photographic images of objects and are often described as the best models of biological vision. This conclusion is largely based on three sets of findings: (1) DNNs are more accurate than any other model in classifying images taken from various datasets, (2) DNNs do the best job in predicting the pattern of human errors in classifying objects taken from various behavioral datasets, and (3) DNNs do the best job in predicting (...) brain signals in response to images taken from various brain datasets (e.g., single cell responses or fMRI data). However, these behavioral and brain datasets do not test hypotheses regarding what features are contributing to good predictions and we show that the predictions may be mediated by DNNs that share little overlap with biological vision. More problematically, we show that DNNs account for almost no results from psychological research. This contradicts the common claim that DNNs are good, let alone the best, models of human object recognition. We argue that theorists interested in developing biologically plausible models of human vision need to direct their attention to explaining psychological findings. More generally, theorists need to build models that explain the results of experiments that manipulate independent variables designed to test hypotheses rather than compete on making the best predictions. We conclude by briefly summarizing various promising modeling approaches that focus on psychological data. (shrink)

On several key issues we agree with the commentators. Perhaps most importantly, everyone seems to agree that psychology has an important role to play in building better models of human vision, and (most) everyone agrees (including us) that deep neural networks (DNNs) will play an important role in modelling human vision going forward. But there are also disagreements about what models are for, how DNN–human correspondences should be evaluated, the value of alternative modelling approaches, and impact of marketing hype in (...) the literature. In our view, these latter issues are contributing to many unjustified claims regarding DNN–human correspondences in vision and other domains of cognition. We explore all these issues in this response. (shrink)

Human beings possess external stores in which they put all sorts of goods to use them at some later time. In this paper we investigate this typically human adaptation using agent-based simulations. We show that the use of external stores explains many aspects of human life, allowing the agents to reduce their dependence on both the environment and the current state of their body and to be more efficient in extracting the energy contained in the environment. We analyse the spatial (...) behaviour of agents with external stores located in specific positions of the environment and we find that these agents tend to develop a sedentary life. We discuss how stores can be at the origin of many human mental and social phenomena such as the acquisition of a more extended temporal perspective, specialisation in producing different types of goods, and exchange of goods. (shrink)

Human beings possess external stores in which they put all sorts of goods to use them at some later time. In this paper we investigate this typically human adaptation using agent-based simulations. We show that the use of external stores explains many aspects of human life, allowing the agents to reduce their dependence on both the environment and the current state of their body and to be more efficient in extracting the energy contained in the environment. We analyse the spatial (...) behaviour of agents with external stores located in specific positions of the environment and we find that these agents tend to develop a sedentary life. We discuss how stores can be at the origin of many human mental and social phenomena such as the acquisition of a more extended temporal perspective, specialisation in producing different types of goods, and exchange of goods. (shrink)

Human beings possess external stores in which they put all sorts of goods to use them at some later time. In this paper we investigate this typically human adaptation using agent-based simulations. We show that the use of external stores explains many aspects of human life, allowing the agents to reduce their dependence on both the environment and the current state of their body and to be more efficient in extracting the energy contained in the environment. We analyse the spatial (...) behaviour of agents with external stores located in specific positions of the environment and we find that these agents tend to develop a sedentary life. We discuss how stores can be at the origin of many human mental and social phenomena such as the acquisition of a more extended temporal perspective, specialisation in producing different types of goods, and exchange of goods. (shrink)