Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

http://science.sciencemag.org/content/sci/201/4359/899.2.full.pdf

Phenomenology of perception.

The task of quantizing general relativity raises serious questions about the meaning of the present formulation and interpretation of quantum mechanics when applied to so fundamental a structure as the space-time geometry itself. This paper seeks to clarify the foundations of quantum mechanics. It presents a reformulation of quantum theory in a form believed suitable for application to general relativity. The aim is not to deny or contradict the conventional formulation of quantum theory, which has demonstrated its usefulness in an overwhelming variety of problems, but rather to supply a new, more general and complete formulation, from which the conventional interpretation can be deduced. The relationship of this new formulation to the older formulation is therefore that of a metatheory to a theory, that is, it is an underlying theory in which the nature and consistency, as well as the realm of applicability, of the older theory can be investigated and clarified.

"relative State" Formulation of Quantum Mechanics

Telephone calls, data and other multimedia information is routed through a hybrid network which includes transfer of information across the internet. A media order entry captures complete user profile information for a user. This profile information is utilized by the system throughout the media experience for routing, billing, monitoring, reporting and other media control functions. Users can manage more aspects of a network than previously possible, and control network activities from a central site. The hybrid network also contains logic for responding to requests for quality of service and reserving the resources to provide the requested services.

System and method for providing requested quality of service in a hybrid network

The Strategy of the Genes

This work is an attempt for a state-of-the-art survey of natural and life sciences with the goal to define the scope and address the central questions of an original research program. It is focused on the phenomena of emergence, adaptive dynamics and evolution of self-assembling, self-organizing, self-maintaining and self-replicating biosynthetic systems viewed from a newly-arranged perspective and understanding of computation and communication in the living nature. The author regards this research as an integral part of the emerging discipline of nature-inspired or natural computation, i.e. computation inspired by or occurring in nature. Within this context, he is interested in studies which represent a significant departure from traditional theories about complex systems and self-organization, emergent phenomena and artificial biology. In particular, these include non-conventional approaches exploring the aggregation, composition, growth and development of physical forms and structures, autopoiesis along with the associated abstract information structures and processes. This paper provides a critical review of the major assumptions which guide the development of modern computer science and engineering towards emulating biological systems. For this purpose, the author explores the potential and the virtues of biology to reshape contemporary science. The goal of this survey is to discuss the present state of natural and engineering sciences in the light of a necessary paradigm change in the structure and methodology of research and deliver some insights for developing a new kind of integral science based on the principles for dynamic interdependence of the constituting disciplines and on the evolving relationships among them.

/pdf/integral-biomathics-a-post-newtonian-view-into-the-logos-of-1jb0391113.pdf

Integral biomathics: a post-Newtonian view into the logos of bios.

Integral Biomathics: Tracing the Road to Reality

This paper presents the results of a joint project initiative, @INGate, in the area of computer/telephony network integration (CTNI) carried out by Siemens AG and the Technical University of Berlin. We propose a distributed intelligent network architecture (DINA) that implements a unified media communications service (UMCS) providing both messaging and telephony services along with network computing and service management throughout circuit switching and packet networks. The architecture comprises a series of interconnected and locally managed intelligent service nodes as interworking units (IWU) between heterogenous networks allowing the user access to a unified media store/bus (UMS/B) via traditional PSTN/ISDN/GSM equipment such as telephones, pagers and fax machines on the one hand and networked computers and PDAs equipped with mail readers and Web browsers on the other hand to enable both on-line and off-line communication. The core of this architecture is the network-bridge service node (NB-SN), a distributed intelligent network element (DINE) consisting of a channel matrix switch (CMS) and a data packet switch (DPS) to link to fixed/mobile telephony and data networks correspondingly, several resource platforms (RPs) connected to media conversion processors (MCPs) to perform media translation in required interchange formats, an Internet gateway (IG) for IP telephony and data access (including customer service control and agent-based network computing) holding the subscribers' mailboxes and providing the Internet connectivity, and a network-bridge service node controller (NB-SNC) to control the overall service logic and the above components. The NB-SN itself is managed along with other nodes in a distributed intelligent network (IN) by a TMN-compliant operation, administration and maintenance center (OAMC).

/pdf/ingate-a-distributed-intelligent-network-approach-to-bridge-2jumy03u5z.pdf

@INGate: a distributed intelligent network approach to bridge switching and packet networks

ions,	  concepts	  and	  underlying	  assumptions	  “native”	  to	  biology and	  distinct	  from	  the	  mechanical	  language	  of	  physics	  and	  computation as	  we	  know	  them.	  A	  pressing	  agenda	  should	  be	  to	  single	  out	  the	  most concrete	  and	  at	  the	  same	  time	  the	  most	  fundamental	  process-­‐units	  in biology	   and	   to	   recruit	   them	   into	   the	   descriptive	   domain.	   Therefore, the	  first	  challenge	  is	  to	  build	  a	  coherent	  formal	  system	  of	  abstractions and	  operations	  that	  is	  truly	  native	  to	  living	  systems. We	  still	  know	  little	  about	  how	  the world	  works,	  and	  these	  limits	  are acknowledged	  in	  our	  emergent biological	  systems	  and	  in	  the frontiers	  of	  astrophysics.	  A	  new mathematical	  foundation	  could punch	  through	  those	  barriers	  and produce	  completely	  unexpected benefits. The	  reason	  that	  biology	  has	  failed	  to develop	  a	  viable	  set	  of	  mathematical methods	  appropriate	  to	  solving	  its problems	  is	  that	  we	  have	  relied	  too long	  on	  mathematics	  developed	  to model	  physical	  problems	  that	  are intrinsically	  different. The	  goal	  of	  the	  INBIOSA	  project	  is	  to devise	  a	  long	  term	  research	  program for	  naturalistic	  biocomputation based	  on	  a	  general	  theory	  of entangled	  coherent	  complex systems,	  both	  living	  and	  non-­‐living ones,	  from	  quantum	  computers	  to the	  human	  brain. We	  focus	  on	  an	  integral/wholist, approach	  to	  dynamic,	  ordered, layered	  systems	  and	  on	  the development	  of	  their	  emergent properties	  and	  structure.	  	  At	  its	  core is	  a	  set	  of	  principles,	  “axioms	  of	  life” upon	  which	  we	  build	  a	  testable

/pdf/stepping-beyond-the-newtonian-paradigm-in-biology-towards-an-31eg9yqloo.pdf

Stepping beyond the newtonian paradigm in biology towards an integrable model of life: Accelerating discovery in the biological foundations of science

The paper presents a concentric multi-ring overlay networking topology for fast and shortest-path resource discovery in dynamic distributed systems like P2P network. First, we define a highly reliable P2P system called HiPeer, which is deployed on top of the logical overlay with a number of lowest bounds in terms of network performance. Then, we demonstrate that for any De Bruijn digraph of degree dges2 and diameter DDB, HiPeer constructs a highly reliable network, where each node maintains a routing table with a size of at most 2d+3 entries independent of the number N of nodes in the system. Further, we show that for any network with at most d nodes, any existing resource in the network can be found within at most DHiPeer=logd(N(d-1)+d)-1 hops. This result is as close to the Moore bound as the query path length in the other best P2P proposals based on the De Bruijn digraphs. Thus, HiPeer defines a highly connected network with connectivity d and the lowest yet known lookup bound DHiPeer. Moreover, we show that any node's "join or leave" operation in HiPeer implies a constant expected reorganization cost of the magnitude order of O(d) control messages

Plamen L. Simeonov

Papers

Integral biomathics: a post-Newtonian view into the logos of bios.

Integral Biomathics: Tracing the Road to Reality

@INGate: a distributed intelligent network approach to bridge switching and packet networks

Stepping beyond the newtonian paradigm in biology towards an integrable model of life: Accelerating discovery in the biological foundations of science

A Concentric Multi-ring Overlay for Highly Reliable P2P Networks