Anthropomimetic robotics differs from conventional approaches by capitalizing on the replication of the inner structures of the human body, such as muscles, tendons, bones, and joints. Here we present our results of more than three years of research in constructing, simulating, and, most importantly, controlling anthropomimetic robots. We manufactured four physical torsos, each more complex than its predecessor, and developed the tools required to simulate their behavior. Furthermore, six different control approaches, inspired by classical control theory, machine learning, and neuroscience, were developed and evaluated via these simulations or in small-scale setups. While the obtained results are encouraging, we are aware that we have barely exploited the potential of the anthropomimetic design so far. But, with the tools developed, we are confident that this novel approach will contribute to our understanding of morphological computation and human motor control in the future.

In this article we examine the effects of the emergence of a new replicator, memes, on the evolution of a pre-existing replicator, genes. Using a version of the NKCS model we examine the effects of increasing the rate of meme evolution in relation to the rate of gene evolution, for various degrees of interdependence between the two replicators. That is, the effects of memes' (suggested) more rapid rate of evolution in comparison to that of genes is investigated using a tunable model of coevolution. It is found that, for almost any degree of interdependence between the two replicators, as the rate of meme evolution increases, a phase transition-like dynamic occurs under which memes have a significantly detrimental effect on the evolution of genes, quickly resulting in the cessation of effective gene evolution. Conversely, the memes experience a sharp increase in benefit from increasing their rate of evolution. We then examine the effects of enabling genes to reduce the percentage of gene-detrimental evolutionary steps taken by memes. Here a critical region emerges as the comparative rate of meme evolution increases, such that if genes cannot effectively select memes a high percentage of the time, they suffer from meme evolution as if they had almost no selective capability.

Many structures built by social insects are the outcome of a process of self-organization, in which the repeated actions of the insects interact over time with the changing physical environment to produce a characteristic end state. A major mediating factor is stigmergy, the elicitation of specific environment-changing behaviors by the sensory effects of local environmental changes produced by previous behavior. A typical task involving stigmergic self-organization is brood sorting: Many ant species sort their brood so that items at similar stages of development are grouped together and separated from items at different stages of development. This article examines the operation of stigmergy and self-organization in a homogeneous group of physical robots, in the context of the task of clustering and sorting Frisbees of two different types. Using a behavioral rule set simpler than any yet proposed for ant sorting, and having no capacity for spatial orientation or memory, the robots are able to achieve effective clustering and sorting showing all the signs of self-organization. It is argued that the success of this demonstration is crucially dependent on the exploitation of real-world physics, and that the use of simulation alone to investigate stigmergy may fail to reveal its power as an evolutionary option for collective life forms.