The biological evolution of information processing

in the evolution of language & learning,

and

my search for= the missing link between body and mind

Section 8:

Evolving from= a minimal system

based on proc= ess control using an inner language

Rainer von K&= ouml;nigslöw, Ph.D.

Abstract=

I speculate that there is a missing link, something that connects physical activity to mental activity. Furthermore, I speculate that this missing link is related to the biological evolution of language and learning. I investigate questions that are u= sually addressed in the field of neuroscience with empirical investigations. I propose a paradigm that investig= ates these questions from the perspective of information processing, and thus al= so fits into the field of artificial intelligence. I propose a design that uses an ‘inner language’ to control action sequences and to integrate visual perception into action. I investigate how this ‘inner language’ facilitates and enhances learning. The investigation demonstrates and validates the feasibility and benefits of the ‘inner language’ design with working prototypes.

TOC

Introduction: summary of previous sections. 5=

Chapter 1: The minimum functionality = of the ‘inner language’ at layer 1. 6=

Chapter 2: The minimum functionality = of the ‘inner language’ at layer 2. 10=

Chapter 3: The evolution of ‘in= ner language’ functionality -- conditions and other more complex instruct= ions. 10=

Chapter 4: The evolution of the capac= ity for learning. <= /span>11=

Chapter 5: Learning requirements for language-based action.. 15=

Chapter 6: The evolution of spoken and written language. 16=

Chapter 7: Turning outer-language-bas= ed learning into inner-language-based action-oriented learning, and vice versa= . 16=

Chapter 8: The concept of ‘shar= ed reality’ 17=

Chapter 9: Body and mind, the missing= link. 18=

Chapter 10: The research paradigm = 211; experimentation & validation.. 20=

Chapter 11: The research paradigm = 211; modeling information content, flow, and processing 22=

Chapter 12: Notes & comments R= 11; status & future plans. 24=

Expanded TOC<= o:p>

Introduction: summary of previous sections. 5=

Chapter 1: The minimum functionality = of the ‘inner language’ at layer 1. 6=

Topic 1: output ‘statements&#= 8217; to the muscles. 6=

Topic 2: input ‘statements= 217; to layer 1. 6=

Topic 3: layer 1 path coordination = for a single joint, and path ambiguity. 7=

Topic 4: layer 1 path coordination = across multiple joints. 7=

Topic 5: improving the actions with limited information processing resources. 9=

Chapter 2: The minimum functionality = of the ‘inner language’ at layer 2. 10=

Topic 1: output ‘statements&#= 8217; to the layer 1 processors. 10=

Chapter 3: The evolution of ‘in= ner language’ functionality -- conditions and other more complex instruct= ions. 10=

Topic 1: if … then … conditions in instructions for integrating vision.. 10=

Topic 2: the ‘inner’ la= nguage as a programming language. 10=

Topic 3: the evolution of the functionality of the ‘inner’ programming language <= !--[if supportFields]>= PAGEREF _Toc213401325 \h 11=

Chapter 4: The evolution of the capac= ity for learning. 11=

Topic 1: action sequences for plans, memory and prediction.. 11=

Topic 2: language-based action-plan= s and learning by trial and error 14=

Topic 3: apprenticeship, modeling, = and other vision-based learning. 15=

Chapter 5: Learning requirements for language-based action.. 15=

Topic 1: learning the translation rules for processing instructions in the inner language 15=

Chapter 6: The evolution of spoken and written language. 16=

Topic 1: inner and outer language. 16=

Topic 2: babbling to speech.. 16=

Chapter 7: Turning outer-language-bas= ed learning into inner-language-based action-oriented learning, and vice versa= . 16=

Topic 1: translating information in outer-language into information in the inner language 17=

Topic 2: translating information in inner-language into information expressed in the outer language <= !--[if supportFields]>= PAGEREF _Toc213401337 \h 17=

Chapter 8: The concept of ‘shar= ed reality’ 17=

Topic 1: what is ‘shared reality’ and ‘understanding each other’ = 17=

Chapter 9: Body and mind, the missing= link. 18=

Topic 1: my dream about finding the ‘missing link’ 18=

Topic 2: the ‘missing link= 217; – connecting mental controls to observable physical action 18=

Topic 3: the ‘missing link= 217; – connecting observable physical action and objects to mental descriptions. 18=

Topic 4: the mind - growing up in a submarine. <= /span>19=

Chapter 10: The research paradigm = 211; experimentation & validation.. 20=

Topic 1: computational equivalence<= span style=3D'color:windowtext;display:none;mso-hide:screen;text-decoration:none; text-underline:none'>. 20=

Topic 2: minimalist feasibility. 20=

Topic 3: empirical validation -- comparing simulated inner-language-based action with observable action.. 21=

Chapter 11: The research paradigm = 211; modeling information content, flow, and processing 22=

Topic 1: complexity and information content 22=

Topic 2: layering and information c= ontent = 22=

Topic 3: layering, compression, and information storage capacity. 22=

Topic 4: layering and information f= low.. 23=

Topic 5: layering and information processing. 23=

Topic 6: learning and the evolution= of layering. <= /span>23=

Chapter 12: Notes & comments R= 11; status & future plans. 24=

Topic 1: present work and future pl= ans. 24=

Topic 2: notes. 24=

Introduction: = summary of previous sections

Chapter 1: The= minimum functionality of the ‘inner language’ at layer 1

Topic 1:&nbs= p; output ‘statements’ to the muscles

= In our minimal model, I have 2 muscles controlling the rotation of a joint in a specific plane. Both muscles are expec= ted to be active at some level all the time, even during periods of sleep. In our model, the muscle does not = have a memory, so that it has to be constantly reminded about what to do. The output statements therefore sp= ecify muscle tension. I assume these ‘reminders’ to come every few milliseconds. To make it to track and to record = the action and the information flow, I assume all the statements to the muscles= to be issued every 30 msec or so. This makes timing and coordination very simple. (I want to be able to record at = 30 frames per second, the normal DVD speed for videos.)

= The paired tension specifications result in a joint rotation angle in a specific plane of rotary motion. For instance, the knee can bend, and how much it is bent can be described by an angle. If the knee is facing forward, then the different bent positions of the lower leg describe an arc= in the plane described by the direction of forward travel and the plumb line f= rom the knee to the ground (stage). The relationship between the paired muscle tensions and joint rotation depends = on a variety of factors including gravity and momentum.

= The range and resolution of the tension specification (joint rotation angle) in= the output statements is another consideration for future models. The model is further simplified by= omitting fault tolerance and redundancy as well as feedback information flowing in t= he other direction. <= /span>

Topic 2:&nbs= p; input ‘statements’ to layer 1

= For the minimal model, the input to layer 1, which is the output of layer 2, specif= ies change points in the sequence of joint rotation angles over time. Start time, end time, and end obje= ctive is required. As further simplification for this initial model, I only deal with a linear progressio= n of joint rotation angles over time. Eventually the different transition paths will have to be considered, i.e. the acceleration and deceleration in the rate of joint rotation. For future versions, control strat= egies might be selected through this interface.&= nbsp; An even more advanced possibility is that control strategies and algorithms might be downloaded through this interface.

Topic 3:&nbs= p; layer 1 path coordination for a single joint, and path ambiguity=

= A quick demonstration might help to illustrate the issue. If I stand and let my hand drop by= my side, I have at least two ways of raising my hand to the top of my head. If you are somewhere where you can= stand up and follow my example without embarrassment, it will help. I can keep my arm straight and swi= ng it up in front of me until it points straight up. Alternatively, still keeping my arm straight, I can swing it out the side until it is straight up. Notice that for the second movemen= t, the hand ends up turned the other way. From either position I can easily turn the lower arm and the wrist to end up with the same hand orientation.&nbs= p; I you enjoyed trying that, you can experiment with even more trajectories by bending the elbow and rotating the shoulder. For instance, the hand can reach a= cross the body while moving up.

Topic 4:&nbs= p; layer 1 path coordination across multiple joints

= There is a nice party game illustration of coordination across multiple joints. Take one of your hands and make a = circle with your hand, say on your desk. Continue moving the hand in circles. Take the second hand and make a ci= rcle beside the first hand, but in the same plane, say on the desk. Now take the second hand and tap t= he desk, but in the same rhythm. Now change the tapping rhythm to make it twice as fast. Now take the second hand and go ba= ck to making circles in the same rhythm as the first hand. Now continue the circl= es but in a different plane, say up and down.= Some coordination, both in timing and type of motion, is easier than others.

= Coordination is easier if there are very few distinct types of motion, and if the timing= of the motion sequences synchronizes naturally and no timing offsets occur. Think of it as a problem of combinatorics. I can make a s= et of distinct coordinated motion sequences. Any observed behaviour must involve= a progression of coordinated motion sequences from this set.

= In the minimal model I have about 40 joint rotation angles to specify. For each, I use the differential t= ension in a pair of muscles. A minim= um might be to control 256 distinct tensions for each muscle. Let us assume that I want to coord= inate a 1 minute behaviour sequence at the 30 msec intervals of layer 1. I have to remember rotation specifications for 2000 time intervals.&nb= sp; In information terms I need 8 * 2 * 40 * 2000 =3D 1,280,000 bits for= a single coordinated 1 minute sequence. For the next minute, the sequence would have to be repeated or a new sequence chosen. <= /span>

= This kind of looping through relatively short action sequences may be reasonable= for creatures with little choice in alternative sequences. 100 distinct sequences in the set = of alternate behaviours requires more than 10⁸ bits. At one neuron per bit, the availab= ility of brain cells just for memory is a major restraint on the complexity of the behaviour repertoire that can be supported. While humans have between 10^1=
1 and 10¹² neurons, the initial vertebrates are likely to have had considerably less. Early in evolution, the neural refresh rate might also have been slower, which furth= er reduces the memory requirements. However, with a fairly large behaviour repertoire that requires dist= inct sequences, the brain will require a lot of bits for remembering them all.

= Above I assumed that 256 different tensions can be specified. Some part of the range of tensions= has to compensate for external factors such as gravity. I thus have a very limited effecti= ve range of differential tensions to control joint-rotation angles. For further improvements in the coordinated action, I would like greater precision. But for greater precision I need m= ore bits, which increases the need for brain cells.

= A second constraint arises from the processing required for sending the tension upda= tes to every pair of muscles every 30msec.&nbs= p; 8 * 2 * 40 * 33 =3D 21,120 bits per second have to flow to the muscles. (This is comparable = to the speed of a telephone modem such as used for sending a fax.) So data transmission speed is a constraint. Increased precisi= on requires even higher data transmission speeds.

= The bits have to be ‘read’ from memory and distributed to the muscles. So information processing speed is= a third constraint. I would like redundancy to reduce the chance for error, and to automatically adjust when problems such as injuries are detected.&nb= sp; But that takes additional processing steps and thus additional processing speed to maintain the information flow to the muscles.

= Adjustments may have to be made to slightly adapt the muscle behaviour due to proprioceptive and other feedback information (such as pain), flowing in the other direction. Force feedba= ck and other control strategies may have been added during evolution. Swimming against a current, or wit= h a side current requires slightly different muscles tensions and movements. Similar adjustments are required f= or running uphill, along the side of a hill or on level ground. For all of these adjustments one c= ould store separate action sequences, but that would be very inefficient compare= d to making adjustments to a sequence. But making the adjustments takes additional processing. At limited processing speeds, ther= e is no time for predictive adjustments or for anything but very short-term reac= tive adjustments.

= To summarize, our model would predict that initial vertebrates would have:

· Limited memory capacity due to a limit in neurons, leading to:

o&nb= sp; short duration coordinated action sequences

o&nb= sp; a small selection of alternate coordinated action sequences=

o&nb= sp; very limited precision in individual action components (joint rotations)

· Limited data transmission speeds

· Limited information processing capabilities

o&nb= sp; Limited redundancy and error recovery

· Limited adaptability through the use of reactive and predictive feedback=

= Which would imply that initial vertebrates would have:

· A limited set of behavior alternatives

· A limited ability to ignore and recover from injuries and internal malfunctio= ns

· A limited ability to adapt the behaviour to changes in circumstances and the immediate environment

Topic 5:&nbs= p; improving the actions with limited information processing resources<= /a>

= For the minimal model, the input to layer 1, which is the output of layer 2, layer = 1 decomposition into separate controllers, each controlled separately by layer 2=

Chapter 2: The minimum functionality of the ‘inner language’ at layer 2=

Topic 1:&nbs= p; output ‘statements’ to the layer 1 processors

= In our minimal model, I have

Chapter 3: The evolution of ‘inner language’ functionality -- conditions and o= ther more complex instructions

Topic 1:&nbs= p; if … then … conditions in instructions for integrating vision

= To make action more successful from an evolutionary perspective, I need conditional= ity. A simple version is ‘if you = see this then follow action sequence 1, otherwise follow action sequence 2’. In essence I are enriching the ‘inner’ language with connectives. From another perspective, I might = see this as a progression where I evolve toward a better internal programming language. Presumably this hap= pened in stages. =

Topic 2:&nbs= p; the ‘inner’ language as a programming language

= I see ballet choreography as the beginnings of a programming language for action sequences. A ballet sequence = is meant to be deterministic, i.e. it is not meant to give the dancer choices on whe= ther to go to this side of the stage or the other. For hunting or food gathering I ne= ed choices. I don’t want t= o eat poison mushrooms, and I don’t want to attack a predator that might eat us. So it is logical that conditions entered early in the development of the ‘inner’ language.

= Similar conditionality might allow feelings to select action sequences. For example, I might have ‘I= f I am hungry then …’, and ‘If I am tired then …’.

Topic 3:&nbs= p; the evolution of the functionality of the ‘inner’ programming language

= Since there are different types of mushrooms that are good to eat, it makes sense= to find an ‘or’ connective early in the development. Similarly with ‘and’, = and ‘not’, since I might want to eat apples that are big and not gr= een.

= At a later stage in the evolution of the ‘inner’ language I might fi= nd the programming capability to write and execute programs. Such capabilities might underlie innovative play and the creation of strategies for hunting that may occur in some cats, monkeys, etc.

Chapter 4: The evolution of the capacity for learning

Topic 1: action sequences for plans, memory a= nd prediction

I hypothesize that there are action sequences that are expressed in an inner language that combines choreography and geometric representations. I hypothesize that these action sequences are independent structures that can exist independent of current perceptions and actions. These action sequences are seen to play a role in planning an action, in remember= ing action, and in predicting the action sequences of others.=

= The action sequence may be constructed on the fly or they may exist before the action sequence is executed or acted out.&= nbsp; A pre-existing action sequence or action plan is like the script in a play. It may be retrieved from memory. The presence of action plans can be investigated for various species with behaviours that require prediction. I developed some experimental designs for which data might already exist and that can hopefu= lly apply to a number of species.

= The first illustration shows the first instance of a predator seeing a prey