Cognitive Robotics: For Never was a Story of More Woe than This  Emanuel Diamant  VIDIA-mant Kiriat Ono , Israel email : emanl.245@gmail.com  Abstract —   We are now on the verge of the next technical revolution   –   robots are going to invade our lives. However, to interact with humans or to be incorporated into a human  “collective” robots have to be provided with some human -like cognitive abilities. What does it mean?   –   Nobody knows. But, robotics research communities are trying hard to find out a way to cope with this problem. Meanwhile, despite abundant funding these efforts did not lead to any meaningful result (only in Europe, only in the past ten years, Cognitive Robotics research funding has reached a ceiling of 1.39 billion euros). In the next ten years, a similar budget is going to be spent to tackle the Cognitive Robotics problems in the frame of the Human Brain Project. There is no reason to expect that this time the result will be different. We would like to try to explain why we are so unhappy about this.  Keywords   –   Cognitive robotics; information; physical infor- mation; semantic information.  I.   I NTRODUCTION  From the beginning, it was a fascinating idea: to create human-like living beings that would help and assist us in our tedious everyday duties. The history has preserved many famous stories about such undertakings   –   Pygmalion and his Galatea, Talos the guard of Crete (both from the ancient  Greek mythology), Maharal’s Golem from the late 16th century Prague, Frankenstein’s monster of the early 19th  century. In the year 1920, that was Karel Capek who gave them their present-day name   –   Robots. In 1942, Isaac Azimov was the first who introduced the term   –   Robotics. In 1959, the first real, not imagined and not legendary, industrial robot had entered the factory floor and, strictly speaking, has heralded the beginning of the robotics era. Then, at the end of the past century, robots start to appear in our human surroundings. It has immediately become clear that, to work with humans (in cooperation and in tight interaction with them), robots have to possess some human-like cognitive abilities. What  does it mean “to possess hu man- like cognitive abilities”? –  Nobody knew then, nobody knows today. But that does not matter   –   the robotics research community enthusiastically started to cope with the challenge, endorsed with ample budget funding provided by the USA Defence Advanced Research   Projects   Agency   (DARPA)   and   the   European Union Research and Technological Development (EU RTD) programme. We would like to provide a short account of these efforts. II.   M ARCH TO THE GLORIOUS FUTURE  As it was just said above, the DARPA in USA and the European   Commission   in   Europe   are   today   the   most prominent supporters of scientific and technological progress, which   are   operating   worldwide   and   are   promoting   an extensive range of critically important research initiatives. In the past 10-15 years, Cognitive Robotics was certainly one among them.  A.   DARPA’s Projects on Cognitive Robotics  The DARPA has always posited itself as an authority aimed to address a wide range of technological opportunities directed to meet the national security challenges. Endorsed with a budget of up to $2.8 billion (in FY 2013), it pursues its objectives through a wide range of R&D programs [1].  Cognitive Robotics does not appear in DARPA’s programme  as a bundle of programs grouped by a common theme; on the  contrary, in DARPA’s pract ice Cognitive Robotics is handled as a collection of separate programs that share a common target issue. The list of Cognitive Robotics and Cognitive- Robotics-related programs launched in the years 2001-2013 can be seen in Table I.  DARPA’s efforts on robotics are focused primarily on  military and defence-related applications with a clear goal to bring real-time, integrated, multi-source intelligence to the battlefield. DARPA does not strive to replace the warrior with a robot, but it believes that it is possible to improve the abilities of individual warfighter by combining technological achievements with human brain cognitive capacities thus making information understanding and decision-making far more effective and efficient for military users. So, it tries hard, on one hand, to revolutionize the underlying technologies (for unmanned   sensor   systems   and   battlefield   information gathering) and, on the other hand, to merge them with the next generation computational systems that will have some human-like cognitive capabilities (such as reasoning and learning capabilities) and levels of autonomy which are  beyond   those   of the   today’s systems.   The   spectrum of  programs   presented   in   Table   I   reliably   represents   this  DARPA’s approach to Cognitiv e Robotics R&D.
TABLE I.   DARPA’ S   P ROJECTS ON   C OGNITIVE   R OBOTICS  Cognitive Computing Systems (CoGS)   2008   –   ....... DARPA's Neovision project (NEOVISION2)   2009   –   ...... Video and Image Retrieval and Analysis Tool (VIRAT) 2011   –   ...... Autonomous Robotics Manipulation Program (ARM)   2011   –   ...... DARPA Robotics Challenge (DRC)   2012   –   ......  DARPA’s Insight Program (DIP)   2013   –   ....... Biologically Inspired Cognitive Architectures (BICA) 2005 - 2007 The Cognitive Technology Threat Warning System (CT2WS) 2007   –   ...... Cognitive Assistant that Learns and Organizes (CALO) 2003 - 2008 Personalized Assistant that Learns (PAL)   2003 - 2008 Augmented Cognition (AugCog)   2001 - 2006  B.   The European programs on Cognitive Robotics  European Union research is conducted in a frame of research programmes called Framework Programmes for Research   and   Technological   Development,   in   short Framework Programmes farther abbreviated as FP1 to FP8. Cognitive Robotics related issues start to appear in the FP5 programme and then, respectively, continue to evolve and expand in the following FP6 and FP7 work programmes.  Contrary to DARPA’s approach, EU R&D activities are clustered to several main “themes” that are further segmented into “challenges”, which are further divided into “objectives”  in frame of which the individual projects are carried out. Cognitive Robotics in the Frame Programmes FP6 and FP7 is   represented   as   a   Challenge   (Challenge   2)   of   the Information and Communication Technologies (ICT) theme (Theme 3). At the time of the transition from FP5 to FP6, when subdivision to Challenges was not yet introduced, Cognitive Robotics and its related issues such as Cognitive Vision and four other particular items appear straight as objectives in the Information Society Technologies (IST) theme (see Table II).  TABLE II.   R OBOTICS IN   FP5  Area   No. of projects   Total cost (M€)   Total EC funding (M€)  IST Demining   8   30,6   15,6 IST FET Neuro-IT   15   32,4   23,1 IST FET General   17   39,2   25,7 IST Cognitive Vision   8   24,2   17,3 GROWTH etc.   24   63,2   34,9 Total   72   189,7   116,5  TABLE III.   C OGNITIVE   R OBOTICS IN   FP6  Year   Objective   Total cost (M€)  2002 Work Programme IST2002 - IV.2.1 Cognitive vision systems IST2002 - VI.2.2 Presence Research: Cognitive sciences and future media ? ? 2003-2004 Work Programme 2.3.1.7 Semantic-based Knowledge Systems 2.3.1.8 Networked Audiovisual systems and home platforms 2.3.2.4 Cognitive Systems 2.3.4.2.(vii) : Bio-inspired Intelligent Information Systems Proactive initiatives (i) Beyond robotics 55 60 25 2005-2006 Work Programme 2.4.6 Networked Audio Visual Systems and Home Platforms 2.4.7 Semantic-based Knowledge and Content Systems 2.4.8 Cognitive Systems 2.4.11 Integrated biomedical information for better health 63 112 45 75  Total   435
TABLE IV.   C OGNITIVE   R OBOTICS IN   FP7  Year   Call   Objective   Budget (M€)  2007   Call 1   ICT-2007.2.1 Cognitive systems, interaction, robotic ICT-2007.4.2 Intelligent content and semantics ICT-2007.8.3 Bio-ICT convergence 96 51 20 2008   Call 3   ICT-2007.2.2 Cognitive systems, interaction, robotics ICT-2007.4.3 Digital libraries and technology-enhanced learning ICT-2007.4.4 Intelligent content and semantics ICT-2007.8.5 Embodied Intelligence 97 50 ? ? 2009   Call 4   ICT-2009.2.1: Cognitive Systems and Robotics ICT-2009.2.2: Language-Based Interaction 73 26 2010   Call 6   ICT-2009.2.1: Cognitive Systems and Robotics ICT-2009.2.2: Language-Based Interaction 80 30 2011   Call 7   ICT-2011-7   Cognitive Systems and Robotics   73 2012   Call 9   ICT-2011-9   Cognitive Systems and Robotics   82 2013   Call 10   ICT-2013.2.1 Robotics, Cognitive Systems & Smart Spaces, Symbiotic Interaction ICT-2013.2.2 Robotics use cases & Accompanying measures 67 23  Total   768  Juxtaposing Table II, Table III, and Table IV, it can be seen how from a Cognitive Vision objective in FP5 (a Cognitive Robotics related topic) Cognitive Robotics has evolved to a full-blown Challenge (Challenge 2) in the FP6  and FP7 programmes, steadily growing from 190 M€ in FP5  to near 1.2 billion euros in the next FP6 and FP7 programmes  (435 M€ for FP6 + 768 M€ for FP7).  III.   D ECEIVED   E XPECTATIONS  During all these times, the declared goals of Cognitive  Robotics programmes were: (As it follows from DARPA’s News Releases) “to create adaptable,   integrated intelligence  systems aimed to augment intelligence analysts’ capabilities  to support time- sensitive operations on the battlefield” [11].  And in another document   –   “The objectives (of DARPA’s  programs) are not to replace human analysts, but to make them more effective and efficient by reducing their cognitive load and enabling them to search for activities and threats  quickly and easily” [12].  Objectives of Challenge 2 programs in the EU research initiative   have   been   far   more   ambitious   –   The   FP6 Workprogramme for years 2003-2004 states: (The objective  is) “to construct physically instantiated or embodied systems  that can perceive, understand (the semantics of information conveyed through their perceptual input) and interact with their environment, and evolve in order to achieve human-like performance in activities requiring context-(situation and task) specific knowledge, etc. The development of cognitive  robots whose “purpose in life” would be to serve   humans as  assistants or “companions” . Such robots would be able to learn new skills and tasks in an active open-ended way and to grow in constant interaction and co-operation with humans ”  [4]. These objectives (almost in similar words) are repeatedly declared in all further Work programmes. For example, the 2011-2012   Workprogramme   says   that   in   these   words:  “Challenge 2 focuses on artificial cognitive systems and  robots that operate in dynamic, nondeterministic, real-life  environments...   Actions   under   this   Challenge   support  research on engineering robotic systems and on endowing  artificial systems with cognitive capabilities” [8].  Careful examination of the outcome that results from both  the DARPA’s programs and from the FP5 -FP7 objectives leads to a univocal conclusion   –   the announced goals of all these programs have never been reached! The explanation of this phenomenon is very simple   –  people try to provide robots with human-like cognitive abilities, but at the same time the same people are devoid of even a slightest understanding about what does the notion of  “human - like cognitive abilities” really mean.  During the past years, the problem has become obvious and   has   been   even   mentioned   in   the   2011-2012  Workprogramme:   “Hard   scientific   and   technological  research issues still need to be tackled in order to make robots fit   for   rendering   high-quality   services,   or   for   flexible manufacturing scenarios. Sound theories are requisite to underpinning   the   development   of   robotic   systems   and providing pertinent   design paradigms,   also   informed   by studies of natural cognitive systems (as in the neuro- and behavioural sciences) [8].
Even more definite was the statement of the year 2013 Work programme   –   “An additional research focus targeted  under this challenge will address symbiotic human-machine relations, which aims at a deeper understanding of human behaviour   during   interaction   with   ICT,   going   beyond conventional approaches. The work on cognitive systems and smart spaces and on symbiotic human-machine relations is  not restricted to robotics” [13].  This promise was also left unfulfilled. At the end of 2013, Cognitive Robotics research has moved to and has tightened itself with the human brain research activities. IV.   N EW   H OPES  At the beginning of year 2014, both Europe and USA will launch ambitious programmes for human brain research. In the USA, the programme is called the Brain Research through Advancing   Innovative   Neurotechnologies   (BRAIN) Initiative and it was announced by President Barack Obama on April 2013. Its accomplishment will be led by the National Institutes of Health   (NIH), DARPA,   and the National Science Foundation (NSF) [14].  In Europe, the Human Brain Project is a ten-year project, consisting of a thirty-month ramp-up phase, funded under FP7, with support from a special flagship ERANET, and a ninety-month operational phase, to be funded under Horizon 2020 programme. The project, which will have a total budget of over 1 billion Euros, is European-led with a strong element of international cooperation. The goal of the project is to build a completely new ICT infrastructure for neuroscience, and for brain-related research in medicine and computing, catalysing a global collaborative effort to understand the human brain and its diseases and ultimately to emulate its computational capabilities [15]. The main features of the two projects are collected in the Table V. As it follows from the Table V, Cognitive Robotics is not among the main goals of the two Flagship initiatives, but it is definitely among   their   main   purposes.   In   the   European  Human   Brain   Project   it   appears   as   the   “Cognitive Architectures” line in the list of the HBP topics. In the  American BRAIN Project Cognitive Robotics issues are  hidden behind the “Link neuronal activity to behaviour” topic.  V.   A N   A TTEMPT TO   P REDICT THE   F UTURE  In attempt to predict the future results of these two projects, let us juxtapose them with something that is well known to us and that we are quite familiar with. We mean the enduring and persistent study of National Economics. While the human nervous system can be seen as the driving force behind the behaviour of a single human, national economics can be seen as the driving force behind the behaviour of a whole human society.   Both   are   complex   distributed   systems   whose efficient   operation   is   supported   by   an   all-embracing communication system. In the Human brain that is the Nervous system, in the National Economics this is   the Transportation system. From Table VI, one can see that the principal features of the Transportation system are well reflected in both brain  research   projects.   Only   one   feature   “What   is   being transported?” is missing in the future brain studies . A proper  answer to the question “What is being transported in the Nervous system between different brain parts?” should be “Information”.   But ,   for   unknown   reasons,   that   is   left undefined   in   both   future   mega-projects.   And   the consequences of this omission are predictable.  TABLE V   E UROPEAN AND   A MERICAN   H UMAN   B RAIN   P ROJECTS  Parameter   European HB Project   American BRAIN Project  Duration   10 years.   long-lasting programme Funding   $ 1.35 billion.   $110 million in the 2014 fiscal year supposed to ramp up this commitment in subsequent years Main Topics   - Human and mouse neural channelomics. - Genotype to phenotype mapping the brain. - Identifying, gathering and organizing neuroscience data. -   Cognitive architectures. - Novel methods for rule-based clustering of medical data. - Neural configurations for neuromorphic computing systems. -   Virtual robotic environments, agents,  sensory & motor systems.  - Theory of multi-scale circuits. - Generate a census of brain cell types - Create structural maps of the brain - Develop new, large-scale neural network recording capabilities - Develop a suite of tools for neural circuit manipulation -   Link neuronal activity to behavior - Integrate theory, modeling, statistics and computation with neuroscience experiments - Delineate mechanisms underlying human brain imaging technologies - Create mechanisms to enable collection of human data for scientific research - Disseminate knowledge and training
TABLE   VI   J UXTAPOSING   H UMAN   B RAIN   P ROJECTS  Economic system   Human brain system  Transportation system   Nervous system  System’s Features   American BRAIN Project   European HB Project Network topology (road and pathway maps) The Brain Connectome Project   Neural channelomics Neuroinformatics platform Network dynamics (Traffic) Transportation means, time tables, hubs, congestions  The DARPA’s SyNAPSE Project   Neuromorphic computing platform What is being transported (through the network) Raw materials, Goods, Freights.  (Information)   (Information)  On the other hand, the reason of this omission is also fully understandable: w e don’t know what Information is and how  it is being transported (processed) in the brain. (That the brain is an information processing system is a widely accepted hypothesis in the scientific community). So, it will be wise to try to understand what information is. VI.   W HAT IS   I NFORMATION  While a consensus definition of information does not exist, we would like to propose a definition of our own (borrowed  and   extended   from   the   Kolmogorov’s   definition   of  information, first introduced in the mid-sixties of the past century):  Information is a linguistic description of structures observable in a given data set   [16]. Two types of structures could be distinguished in a data set  –   primary and secondary data structures. The first are data elements aggregations whose agglomeration is guided by natural physical laws; the others are aggregations of primary dat a structures which appear in the observer’s brain guided by the observer’s customs and habits. Therefore, the first  could be called Physical data structures, and the second, Meaningful   or   Semantic   data   structures.   And   their descriptions   should   be   accordingly   called   Physical Information   and   Semantic Information . This   subdivision   is   usually   overlooked   in   the contemporary   data   processing   approaches   leading   to mistaken   and   erroneous   data   handling   methods   and techniques. In [17], E. Diamant presents a list of publications on the subject and a more extended explanation of information description duality can be found. Meanwhile, it is important to explain the consequences that immediately pop up from this assertion. And which are critically important for the right definition of the notion of cognition. In the light of this just acquired knowledge, we can certainly posit that   cognitive ability is the ability to process information . And that is what our brains are doing, and that is what we are striving to replicate in our Cognitive Robots designs. First of all, physical information is carried by the data and therefore can be promptly extracted from it. At the same time,  semantic   information   is   a   description   of   observer’s  arrangement of the physical data structures and therefore it can not be extracted from the data, because semantics is not a property of the data, it is a property of an observer that is watching and scrutinizing the data. As such, semantics is always   subjective   and   it   is   always   a   result   of   mutual agreements and conventions that are established in a certain group of observers, or a future group of robots and humans that act as a team sharing a common semantic understanding (semantic information) about their environment. An important sequel of this is that the semantic information can not be learned autonomously, but it should be provided to a cognitive robot from the outside (semantics has to be taught and not learned, as it is usually requested by all workprogrammes). Another important corollary that follows from the new understanding   of   information   nature   is   that   information description is always a linguistic description, that is, a string of symbols which can take a form of a mathematical formula  (don’t forget that mathematics is a sort of a language ) or a natural language item   –   a word, a sentence, or a piece of text. That   is   a   very   important   outcome   of   the   new   theory considering that contemporary approaches to the problem of information processing are assuming computer involvement in the processing task. However, contemporary computers are data processing machines which are not supposed to process natural   language   texts   which   are   carrying   semantic information. Finally, we would like to provide some examples of widespread misunderstandings that appear in the Calls of proposals issued by DARPA and EU Commission: In the  “ICT Work Programme 2009/2010, (C(2009) 5893)”   [7], in its   “ Part 4.2 Challenge 2: Cognitive Systems, Interaction,  Robotics”   the problem that Robotic systems have to cope with is specifies   as “extracting meaning and purpose from  bursts of sensor data or strings of computer code ... ”   This is
a false and a misleading statement   –   sensor data does not possess semantics, and therefore, meaning and purpose can not be extracted from it.  DARPA’s   Document   “Deep Learning” (RFI SN08 -42) states that:   “DARPA is interested in new algorithms for  learning from unlabeled data in an unsupervised manner to extract   emergent   symbolic   representations   from   sensory input ... ”   Again, that is a false and a misleading statement   –  symbolic representations (semantics) could not be learned from data. VII.   C ONCLUSION  Cognitive Robotics R&D is a very important branch of contemporary science that is paving the road to the next technological revolution   –   smart robots that are invading our everyday lives. Until now, the extensive research efforts of the Cognitive Robotics field investigators have been derailed by a wrong understanding about the essence of information, in general, and semantic information, in particular. We hope that the paper will contribute to some changes in this situation. R EFERENCES  [1]   DARPA’s   Mission in a Changing World, DARPA Framework 2013, Available: http://www.hsdl.org/?view&did=735402 retrieved: March, 2014.  [2]   P. Karp and T. Skordas,   “ Robotics in the IST Programme ” , 22nd JCF Meeting, 16 - 18 October 2003, Madrid, Spain, Available: http://www.nsf.gov/eng/roboticsorg/documents/EU_000.pdf retrieved: March, 2014.  [3]   2002 Work programme, Available: ftp://ftp.cordis.europa.eu/pub/ist/docs/b_wp_en_200201.pdf retrieved: March, 2014.  [4]   2003-2004 Workprogramme, Available: ftp://ftp.cordis.europa.eu/pub/ist/docs/wp2003- 04_final_en.pdf , retrieved: March, 2014.  [5]   2005-06 Work Programme, Available: ftp://ftp.cordis.europa.eu/pub/ist/docs/ist_wp-2005- 06_final_en.pdf , retrieved: March, 2014.  [6]   2006 Work Programme Fourth Update, Available: ftp://ftp.cordis.europa.eu/pub/ist/docs/wp_4th_update_en.pdf , retrieved: March, 2014.  [7]   Updated work programme 2009 and work programme 2010, Available: ftp://ftp.cordis.europa.eu/pub/fp7/ict/docs/ict-wp- 2009-10_en.pdf, retrieved: March, 2014.  [8]   Updated work programme 2011 and work programme 2012, Available: ftp://ftp.cordis.europa.eu/pub/fp7/ict/docs/ict-wp- 2011-12_en.pdf , retrieved: March, 2014.  [9]   Work programme 2013, Available: http://cordis.europa.eu/fp7/ict/docs/ict-wp2013-10-7-2013.pdf retrieved: March, 2014.  [10]   ICT Challenge 2: Cognitive Systems and Robotics, Available: http://cordis.europa.eu/fp7/ict/programme/challenge2_en.html retrieved: March, 2014.  [11]   DARPA   advances   video   analysis   tools,   Available: http://www.darpa.mil/NewsEvents/Releases/2011/2011/06/23 _DARPA_advances_video_analysis_tools.aspx .   retrieved: March, 2014.  [12]   Unified Military Intelligence Picture Helping to Dispel the Fog of War, Available: http://www.darpa.mil/NewsEvents/Releases/2013/09/05.aspx retrieved: March, 2014.  [13]   ICT Work programme 2013, Available: http://cordis.europa.eu/fp7/ict/docs/ict-wp2013-10-7-2013.pdf retrieved: March, 2014.  [14]   BRAIN   Working   Group   Interim   Report,   Available: http://www.nih.gov/science/brain/09162013- Interim%20Report_Final%20Composite.pdf retrieved: March, 2014.  [15]   The Human Brain Project, Available: https://www.humanbrainproject.eu/documents/10180/17648/T heHBPReport_LR.pdf/18e5747e-10af-4bec-9806- d03aead57655 , retrieved: March, 2014  [16]   E. Diamant,   “ Let Us First Agree on what the Term "Semantics" Means: An Unorthodox Approach to an Age-Old Debate ” , In M. T. Afzal, Ed., "Semantics - Advances in Theories and Mathematical Models", pp. 3   –   16, InTech Publisher, http://www.intechopen.com/statistics/35998 retrieved: March, 2014  [17]   E. Diamant, “Brain, Vision, Robotics, and Artificial Intelligence”,   Available: http://www.vidia-mant.info, retrieved: March, 2014.