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My career as founder and CEO of technology companies began in the early 90’s. Over the years, I’ve become aware of two strong pulls within me. Alongside very analytical, strategic, factual, and pragmatic considerations, I was fascinated by softer, multidimensional, even spiritual elements in business and management.
Throughout my career founding and managing companies, I was attracted to identify the operating ethos of their executives, and to explore the considerations incorporated in the decision-making processes responsible for effectiveness and coherence. Intuitively, I’ve explored the balance between business practices and broader human paradigms.
At some point the intuition ad hoc was conceptualized into a universal methodology.
My background is a BSC in Mechanical Engineering, DIC in Process Control, and a PhD in Artificial Intelligence from Imperial College, University of London. A term at the department of Computer Science at the Wiezman Institute, teaching MBA students and founding start-ups in software, communication, and sustainability.
Problem Solving from Nature
Problem Solving from Nature
In the concrete world where the laws of physics, chemistry, and biology govern, there is a richness of mechanisms which yield highly effective solutions that represent optimal arrangements. These arrangements often fill us with reverence for their effectiveness and sophistication.
The book Problem Solving from Nature offers a diverse collection of problem-solving approaches inspired by nature, implemented to solve intractable man-made problems.
Genetic Algorithms and Robotics
When we come to address complex challenges, we have two distinct alternatives: an analytical approach which assumes one can build a good enough model of the issue and apply structured tools to reach a near optimal solution. And there is the holistic approach which assumes the interrelations between the defining parameters of the challenge are too complex for an analysis, and it is much more enlightening to allow the defining characters of the hidden relationships to surface and expose themselves.
The book “Genetic Algorithms and Robotics” drafts a methodical approach inspired by biological mechanisms of evolution that enables the discovery of the elusive fine balance of an optimal solution. The problem-solving concept is then applied to self-actuating robotic tasks.
