The artificial endocrine system (AES) is a new branch of natural computing which uses ideas
and takes inspiration from the information processing mechanisms contained in the …

We present an adaptive artificial neural-endocrine (AANE) system that is capable of learning
ldquoon-linerdquo and exploits environmental data to allow for adaptive behaviour to be …

For any embodied, mobile, autonomous agent it is essential to control its actuators
appropriately for the faced task. This holds for natural organisms as well as for robots. If …

This work proposes a novel Situation-Aware FEar Learning (SAFEL) model for robots.
SAFEL combines concepts of situation-aware expert systems with well-known …

Some important mechanisms in neuroendocrine-immune (NEI) system are inspired to
design a decentralized, evolutionary, scalable, and adaptive system for Web service …

The robots that operate autonomously for extended periods in remote environments are
often limited to gather only small amounts of power through photovoltaic solar panels. Such …

Future applications of robotic technologies will involve interactions with non-expert humans
as machines will assume the role of companions, teachers or healthcare assistants. In all …

The paper is focused on improving the performance of neuro-endocrine models with
considering the interaction of glands. Comparing to conventional neuro-endocrine models …

This paper presents the novel use of the Neural-endocrine architecture for swarm robotic
systems. We make use of a number of behaviours to give rise to emergent swarm behaviour …

Biological agents are context-dependent systems that exhibit behavioral flexibility. The
internal and external information agents process, their actions, and emotions are all …