Ernest 8.3 is the same as Ernest 8.2; only the interface with his environment has changed.
Ernest 8.3's turning actions make him turn PI/4 rather than PI/2 before. Accordingly, Ernest 8.3 can now move forward in diagonal. Also, Ernest 8.3's eyes have a narrower angular span of PI/8 each (rather than PI/2 with Ernest 8.2).
These settings require a longer learning phase than before because of the topological differences between diagonals and straight lines, and because of the reduced visual field that implies more complex behaviors to find the targets. The fact that the same Ernest algorithm can learn to deal with these different settings demonstrates again the algorithm's robustness.
This example video shows that Ernest is now a pretty serious predator in the grid world. We call him Ernestor-Rex or e-Rex. As opposed to poor Ernest 8.2, The Ernestor-Rex does not get trapped into infinite loops between preys. See step 330 and further. This is because his narrow visual field makes him take care of a single prey at a time.
Wednesday, February 9, 2011
Friday, February 4, 2011
Poor Ernest 8.2
In this example, Ernest found another strategy that consisted of moving on a straight line while systematically checking on his side to see if he became aligned with the blue square.
On step 120, we created a situation where the blue square would get hidden by a wall when Ernest would enact this strategy. When he saw the blue square, Ernest started moving toward it, but then he arrived to a point where the blue square became hidden behind the wall. This situation illustrates again that Ernest is not driven by a final goal but by rudimentary intrinsic motivations. When the blue square attraction disappears, Ernest just stops and spins in place (motivated to look for a new blue square).
On step 230, we inserted two blue squares. In this particular instance, Ernest got locked in an infinite loop between the two blue squares. Again, Ernest's behavior fits the subjective explanation that he just enjoys moving toward blue squares, which he can keep doing continuously in this specific loop.
Yet, we would like Ernest to be smarter and use a bit more determination to find blue squares. The next step might be of learning to recognize specific locations in space. Learning persistence of spatial locations might be an interesting prerequisite before learning persistence of objects. To manage to recognize specific locations, Ernest will need a better visual system.
On step 120, we created a situation where the blue square would get hidden by a wall when Ernest would enact this strategy. When he saw the blue square, Ernest started moving toward it, but then he arrived to a point where the blue square became hidden behind the wall. This situation illustrates again that Ernest is not driven by a final goal but by rudimentary intrinsic motivations. When the blue square attraction disappears, Ernest just stops and spins in place (motivated to look for a new blue square).
On step 230, we inserted two blue squares. In this particular instance, Ernest got locked in an infinite loop between the two blue squares. Again, Ernest's behavior fits the subjective explanation that he just enjoys moving toward blue squares, which he can keep doing continuously in this specific loop.
Yet, we would like Ernest to be smarter and use a bit more determination to find blue squares. The next step might be of learning to recognize specific locations in space. Learning persistence of spatial locations might be an interesting prerequisite before learning persistence of objects. To manage to recognize specific locations, Ernest will need a better visual system.
Friday, January 7, 2011
The tangential strategy learning process
To get a better view on how Ernest learned the tangential strategy, let us examine his activity trace:
1 2(> |+) 3(> |+) 4(> |+) 5(> |+) 6(> |+) 7(> |o) 8(v |*) 9(v*|o) 10(>+| ) 11(^ |*) 12(^o| ) 13(^ |o) 14(^*| ) 15(>o| ) 16(>) 17(>) 18(^*| ) 19(vo| ) 20(v) 21(^) 22(>) 23(^*| ) 24(^o|*) 25(^ |o) 26(^) 27(v) 28(v |*) 29(^ |o) 30(^) 31(>) 32(^*| ) 33(^o|*) 34(v*|o) 35(>+| ) 36(^o|*) 37(v*|o) 38(>+| ) 39(^ |*) 40(v |o) 41(>o| ) 42(>) 43(^*| ) 44(^o|*) 45(> |+) 46(> |+) 47(> |o) 48(v |*) 49(v*|o) 50(>+| ) 51(^ |*) 52(>+|+) 53(v |o) 54(vo| ) 55(v |*) 56(v*| ) 57(v |o) 58(^ |*) 59(>+|+) 60(>+|+) 61(>+|+) 62(>x|x) 63(>o|o) 64(v) 65(v) 66(v) 67[v] 68(^) 69[v] 70(v) 71(v) 72(v) 73[v] 74[>] 75(^*| ) 76(^o|*) 77(> |+) 78(> |+) 79(> |+) 80(> |+) 81(> |+) 82(> |o) 83(v |*) 84(v*|o) 85(>+| ) 86(^ |*) 87(>+|+) 88(>x|x) 89(^o|o)
In this trace, the numbers indicate the cycle counter also displayed in the bottom-right corner of the video. The symbols that represent Ernest’s primitive actions read as follows: ^ turn left, > try to move forward, v turn right. These are within parentheses when they succeed and within angle brackets when they fail. For example, Ernest turned toward an adjacent wall on step 73 and bumped a wall on step 74; in all other steps in this trace, primitive schemas succeeded.
The symbols that represent the eye signals read as follows: * appear, + closer, x arrived, o disappear. These symbols are represented on each side of a | character, the left eye signal being on the left and the right eye signal on the right. For example, on step 9, Ernest turned right, the blue square appeared in the left eye’s field and disappeared from the right eye’s field. On step 10, the blue square got closer in the left field and nothing changed in the right field. On step 11, the blue square appeared in the right field and nothing changed in the left field, meaning that the blue square was then present in both eyes’ fields.
The first interesting (safe and satisfying) sequence was found right at the beginning when Ernest moved forward and got closer in the context where he had just moved forward and gotten closer. This experience made him repeat this sequence from step 2 to step 7 when he received a disappear signal from the right eye.
From step 7 to step 11, Ernest learned the returning sequence: step 7: Move forward, disappear on right. 8 : Turn right, appear on right. 9 : Turn right, appear on left, disappear on right. 10: Move forward, closer on left. 11: Turn left, appear on right. After step 11, Ernest is facing the blue square but doesn’t yet know to move forward in this category of context, and he randomly picked a turn action.
On steps 47 through 51, Ernest enacted again the returning sequence because it had proven to work and to be satisfying in the category of context where he finds himself again. On step 52, he choose to move forward (other options had already proven uninteresting in the current category of context), obtaining a closer signal from both eyes. On step 53, however, he does not yet know to continue moving forward in the current category of context and he randomly picks turn right.
On step 59, he again got closer in both eyes when moving forward (although out of a different preceding sequence). In this context, he picked again move forward on step 60, which proved satisfying, engaging him to continue on step 61 until he stepped on the blue square on step 62.
When the second blue square is introduced on step 75, he has thus already learned to enact the different subsequences needed for the tangential strategy, as well as to categorize contexts accordingly. In effect, he uses these different subsequences in the right way until he reaches the second square on step 88.
This quick learning was somewhat lucky but we choose to report it because it led to a clean example of the tangential strategy. In other runs, Ernest may learn mixed strategies that are less prototypical. This run was, however, not so extraordinarily lucky because behaviors are not picked randomly but rather always exploit what has been learned thus far. Chance is only used to untie conflicting impulses when they cannot be untied from previous knowledge.
Experience shows that Ernest always learns a strategy within the first hundred steps, and that the most frequently found strategy is the diagonal strategy.
1 2(> |+) 3(> |+) 4(> |+) 5(> |+) 6(> |+) 7(> |o) 8(v |*) 9(v*|o) 10(>+| ) 11(^ |*) 12(^o| ) 13(^ |o) 14(^*| ) 15(>o| ) 16(>) 17(>) 18(^*| ) 19(vo| ) 20(v) 21(^) 22(>) 23(^*| ) 24(^o|*) 25(^ |o) 26(^) 27(v) 28(v |*) 29(^ |o) 30(^) 31(>) 32(^*| ) 33(^o|*) 34(v*|o) 35(>+| ) 36(^o|*) 37(v*|o) 38(>+| ) 39(^ |*) 40(v |o) 41(>o| ) 42(>) 43(^*| ) 44(^o|*) 45(> |+) 46(> |+) 47(> |o) 48(v |*) 49(v*|o) 50(>+| ) 51(^ |*) 52(>+|+) 53(v |o) 54(vo| ) 55(v |*) 56(v*| ) 57(v |o) 58(^ |*) 59(>+|+) 60(>+|+) 61(>+|+) 62(>x|x) 63(>o|o) 64(v) 65(v) 66(v) 67[v] 68(^) 69[v] 70(v) 71(v) 72(v) 73[v] 74[>] 75(^*| ) 76(^o|*) 77(> |+) 78(> |+) 79(> |+) 80(> |+) 81(> |+) 82(> |o) 83(v |*) 84(v*|o) 85(>+| ) 86(^ |*) 87(>+|+) 88(>x|x) 89(^o|o)
In this trace, the numbers indicate the cycle counter also displayed in the bottom-right corner of the video. The symbols that represent Ernest’s primitive actions read as follows: ^ turn left, > try to move forward, v turn right. These are within parentheses when they succeed and within angle brackets when they fail. For example, Ernest turned toward an adjacent wall on step 73 and bumped a wall on step 74; in all other steps in this trace, primitive schemas succeeded.
The symbols that represent the eye signals read as follows: * appear, + closer, x arrived, o disappear. These symbols are represented on each side of a | character, the left eye signal being on the left and the right eye signal on the right. For example, on step 9, Ernest turned right, the blue square appeared in the left eye’s field and disappeared from the right eye’s field. On step 10, the blue square got closer in the left field and nothing changed in the right field. On step 11, the blue square appeared in the right field and nothing changed in the left field, meaning that the blue square was then present in both eyes’ fields.
The first interesting (safe and satisfying) sequence was found right at the beginning when Ernest moved forward and got closer in the context where he had just moved forward and gotten closer. This experience made him repeat this sequence from step 2 to step 7 when he received a disappear signal from the right eye.
From step 7 to step 11, Ernest learned the returning sequence: step 7: Move forward, disappear on right. 8 : Turn right, appear on right. 9 : Turn right, appear on left, disappear on right. 10: Move forward, closer on left. 11: Turn left, appear on right. After step 11, Ernest is facing the blue square but doesn’t yet know to move forward in this category of context, and he randomly picked a turn action.
On steps 47 through 51, Ernest enacted again the returning sequence because it had proven to work and to be satisfying in the category of context where he finds himself again. On step 52, he choose to move forward (other options had already proven uninteresting in the current category of context), obtaining a closer signal from both eyes. On step 53, however, he does not yet know to continue moving forward in the current category of context and he randomly picks turn right.
On step 59, he again got closer in both eyes when moving forward (although out of a different preceding sequence). In this context, he picked again move forward on step 60, which proved satisfying, engaging him to continue on step 61 until he stepped on the blue square on step 62.
When the second blue square is introduced on step 75, he has thus already learned to enact the different subsequences needed for the tangential strategy, as well as to categorize contexts accordingly. In effect, he uses these different subsequences in the right way until he reaches the second square on step 88.
This quick learning was somewhat lucky but we choose to report it because it led to a clean example of the tangential strategy. In other runs, Ernest may learn mixed strategies that are less prototypical. This run was, however, not so extraordinarily lucky because behaviors are not picked randomly but rather always exploit what has been learned thus far. Chance is only used to untie conflicting impulses when they cannot be untied from previous knowledge.
Experience shows that Ernest always learns a strategy within the first hundred steps, and that the most frequently found strategy is the diagonal strategy.
The tangential strategy
In this example video, Ernest 8.2 found a strategy that we named the tangential strategy.
The tangential strategy consists of approaching the blue square in a straight line as opposed to a diagonal line (the diagonal strategy in the previous example). The trick with the tangential strategy is that Ernest cannot know when he should turn toward the blue square until he passed it. The tangential strategy thus consists of moving on a straight line until the blue square disappears from the visual field, then returning one step backward, and then turning toward the blue square.
The emergence of a specific strategy occurs during Ernest's youth while he his babbling relatively randomly, in parallel to the emergence of goals. See the details in the next post. When Ernest has organized behavioral patterns that proved both satisfying and robust, he adopts them and stick to them as long as they work.
These results demonstrate that:
a) Ernest does not encode strategies nor task procedures defined by the programmer, as opposed to traditional cognitive modeling.
b) Ernest instances are capable of "individuating" themselves through their experience, i.e., acquiring their own cognitive individuality that was not encoded in their "genes". This accounts for the role of individual experience in cognitive development.
c) Ernest's goals emerge from his low-level drives. Eating blue squares appears to the observer as becoming the goal of Ernest' life while no representation of such goal was encoded into Ernest. Indeed, Ernest was given a high incentive to step on blue squares but this incentive was not different in nature from other primitive drives. Ernest's goals were not pre-encoded as they are, for example, in the goal buffer of the ACT-R architecture.
The tangential strategy consists of approaching the blue square in a straight line as opposed to a diagonal line (the diagonal strategy in the previous example). The trick with the tangential strategy is that Ernest cannot know when he should turn toward the blue square until he passed it. The tangential strategy thus consists of moving on a straight line until the blue square disappears from the visual field, then returning one step backward, and then turning toward the blue square.
The emergence of a specific strategy occurs during Ernest's youth while he his babbling relatively randomly, in parallel to the emergence of goals. See the details in the next post. When Ernest has organized behavioral patterns that proved both satisfying and robust, he adopts them and stick to them as long as they work.
These results demonstrate that:
a) Ernest does not encode strategies nor task procedures defined by the programmer, as opposed to traditional cognitive modeling.
b) Ernest instances are capable of "individuating" themselves through their experience, i.e., acquiring their own cognitive individuality that was not encoded in their "genes". This accounts for the role of individual experience in cognitive development.
c) Ernest's goals emerge from his low-level drives. Eating blue squares appears to the observer as becoming the goal of Ernest' life while no representation of such goal was encoded into Ernest. Indeed, Ernest was given a high incentive to step on blue squares but this incentive was not different in nature from other primitive drives. Ernest's goals were not pre-encoded as they are, for example, in the goal buffer of the ACT-R architecture.
Wednesday, January 5, 2011
Ernest 8.2 can find his food
Ernest 8.2 is a horseshoe crab. Horseshoe crabs are archaic arthropods whose visual system has been extensively studied. From these studies, we pulled several principles that guided the development of Ernest's distal sensory system:
- Small matrix resolution: the horseshoe crab's most elaborated eyes (two compound eyes among the 10 eyes that horseshoe crabs possess) have a resolution of roughly 40*25 pixels.
- Fixed eyes: eyes are fixed to the animal's body. The animal has to rotate its full body to move its visual field.
- Sensibility to movement: the signal sent to the brain does not reflect static shape recognition but rather reflects changes in the visual field.
- Visio-spatial behavioral proclivity: male horseshoe crabs move toward females when they see them with their compound eyes whereas females move away from other females.
As noted earlier, Ernest's "eyes" have only one pixel — pixel sensible to the distance to the blue square in a 90° visual field (assuming there is only one blue square).
Each eye produces a signal that represents the change in the corresponding visual field during the last interaction cycle:
- Appear: a blue square appeared in the visual field.
- Closer: more blue in the visual field, meaning the blue square is approaching.
- Arrived: the blue square occupies the entire visual field, meaning Ernest is stepping on the blue square and can eat it.
- Disappeared: the blue square disappeared from the visual field.
As opposed to previous versions, Ernest 8.2 has no antenna and has only three possible primitive behaviors:
- [move forward, succeed, 0] Ernest is indifferent of moving forward.
- [move forward, fail, -8] Ernest hates bumping walls.
- [turn left or right, succeed, 0] Ernest is indifferent of turning toward an adjacent empty square.
- [turn left or right, fail, -5] Ernest dislikes turning toward an adjacent wall.
To generate a visio-spatial behavioral proclivity, Ernest's sequential learning mechanism receives an additional inborn intrinsic satisfaction when an eye returns a signal:
- [Appear, 15] Ernest loves blue squares appearing in an eye's visual field.
- [Closer, 10] Ernest enjoys blue squares getting closer.
- [Arrived, 30] Ernest is crazy about stepping on a blue square (and eating it in the process).
- [Disappear, -15] Ernest hates blue squares disappearing from an eye's visual field.
At the beginning, the video shows Ernest learning to coordinate his actions with his sensory input. As before, he needs to learn to generate expectations associated with actions (e.g., turning schemas may shift the blue square from one eye to the other, etc.). He also needs to learn sequences of behavior (or "strategies") to reach the blues square. In this example run, he learned a strategy consisting of following a diagonal, and subsequently a straight line. Other strategies are possible that we will report next.
- Small matrix resolution: the horseshoe crab's most elaborated eyes (two compound eyes among the 10 eyes that horseshoe crabs possess) have a resolution of roughly 40*25 pixels.
- Fixed eyes: eyes are fixed to the animal's body. The animal has to rotate its full body to move its visual field.
- Sensibility to movement: the signal sent to the brain does not reflect static shape recognition but rather reflects changes in the visual field.
- Visio-spatial behavioral proclivity: male horseshoe crabs move toward females when they see them with their compound eyes whereas females move away from other females.
As noted earlier, Ernest's "eyes" have only one pixel — pixel sensible to the distance to the blue square in a 90° visual field (assuming there is only one blue square).
Each eye produces a signal that represents the change in the corresponding visual field during the last interaction cycle:
- Appear: a blue square appeared in the visual field.
- Closer: more blue in the visual field, meaning the blue square is approaching.
- Arrived: the blue square occupies the entire visual field, meaning Ernest is stepping on the blue square and can eat it.
- Disappeared: the blue square disappeared from the visual field.
As opposed to previous versions, Ernest 8.2 has no antenna and has only three possible primitive behaviors:
- [move forward, succeed, 0] Ernest is indifferent of moving forward.
- [move forward, fail, -8] Ernest hates bumping walls.
- [turn left or right, succeed, 0] Ernest is indifferent of turning toward an adjacent empty square.
- [turn left or right, fail, -5] Ernest dislikes turning toward an adjacent wall.
To generate a visio-spatial behavioral proclivity, Ernest's sequential learning mechanism receives an additional inborn intrinsic satisfaction when an eye returns a signal:
- [Appear, 15] Ernest loves blue squares appearing in an eye's visual field.
- [Closer, 10] Ernest enjoys blue squares getting closer.
- [Arrived, 30] Ernest is crazy about stepping on a blue square (and eating it in the process).
- [Disappear, -15] Ernest hates blue squares disappearing from an eye's visual field.
At the beginning, the video shows Ernest learning to coordinate his actions with his sensory input. As before, he needs to learn to generate expectations associated with actions (e.g., turning schemas may shift the blue square from one eye to the other, etc.). He also needs to learn sequences of behavior (or "strategies") to reach the blues square. In this example run, he learned a strategy consisting of following a diagonal, and subsequently a straight line. Other strategies are possible that we will report next.
Monday, December 20, 2010
Ernest 8.1 can eat
Ernest can now perform different actions with different body parts simultaneously. Namely, he can eat this delicious blue substance with his virtual mouth while enacting his usual wandering behavior with his antennas and virtual legs.
To obtain this result, Ernest was provided with a modular internal structure. Ernest now has an iconic module that implements his first skills to exploit his distal sensory system, and a "homeostatic" module that controls his homeostatic regulation behavior. Ernest 8.1, yet, only has one single homeostatic behavior: eating the blue substance. Each module has its own enaction canal, making simultaneity across modules possible.
The homeostatic primitive schema was added to the other primitive schemas listed previously:
- [Eat, succeed, 100] Ernest is crazy about eating.
and one iconic pattern was predefined:
- [0,0] Blue_icon (each pixel represents the distance to the blue square in the corresponding sensory field).
Ernest now also supports inborn composite schemas. In this experiment, these are:
- [Touch ahead empty, Move forward, 3]
- [Turn left toward empty, Move forward, 3]
- [Turn right toward empty, Move forward, 3]
- [Blue_icon, Eat, 3]
The three first inborn composite schemas are just provided to accelerate the initial learning. The fourth is provided to make Ernest eat when he senses that he is on a blue square. These four composite schemas were preset with an initial weight of 3.
The sensory system being linked to the homeostatic system through the [Blue_icon, Eat] composite schema makes Ernest 8.1's distal sensory system somehow resemble smell (in addition to vision) because the sensory system detecting the null distance to food triggers eating.
These developments were inspired by Joanna Bryson's paper Structuring Intelligence: The Role of Hierarchy, Modularity and Learning in Generating Intelligent Behaviour. Joanna's discussion on the agent's modular architecture inspired our implementation of Ernest's modules. Also, we follow her argument that sometimes it is ok to pre-encode the desired behavior into the agent.
Now the question is how to implement the effects that the satisfaction gained through eating should have on Ernest to make him exploit his distal sensors in the search for food.
To obtain this result, Ernest was provided with a modular internal structure. Ernest now has an iconic module that implements his first skills to exploit his distal sensory system, and a "homeostatic" module that controls his homeostatic regulation behavior. Ernest 8.1, yet, only has one single homeostatic behavior: eating the blue substance. Each module has its own enaction canal, making simultaneity across modules possible.
The homeostatic primitive schema was added to the other primitive schemas listed previously:
- [Eat, succeed, 100] Ernest is crazy about eating.
and one iconic pattern was predefined:
- [0,0] Blue_icon (each pixel represents the distance to the blue square in the corresponding sensory field).
Ernest now also supports inborn composite schemas. In this experiment, these are:
- [Touch ahead empty, Move forward, 3]
- [Turn left toward empty, Move forward, 3]
- [Turn right toward empty, Move forward, 3]
- [Blue_icon, Eat, 3]
The three first inborn composite schemas are just provided to accelerate the initial learning. The fourth is provided to make Ernest eat when he senses that he is on a blue square. These four composite schemas were preset with an initial weight of 3.
The sensory system being linked to the homeostatic system through the [Blue_icon, Eat] composite schema makes Ernest 8.1's distal sensory system somehow resemble smell (in addition to vision) because the sensory system detecting the null distance to food triggers eating.
These developments were inspired by Joanna Bryson's paper Structuring Intelligence: The Role of Hierarchy, Modularity and Learning in Generating Intelligent Behaviour. Joanna's discussion on the agent's modular architecture inspired our implementation of Ernest's modules. Also, we follow her argument that sometimes it is ok to pre-encode the desired behavior into the agent.
Now the question is how to implement the effects that the satisfaction gained through eating should have on Ernest to make him exploit his distal sensors in the search for food.
Friday, December 10, 2010
Ernest 8.0 has rudimentary distal perception
Ernest 8.0's distal sensory system consists of two pixels that react to blue squares. Each pixel reflects 90° of Ernest's surrounding environment. Ernest's left-side pixel reflects the front-left 90° quadrant, and Ernest's right-side pixel reflects the front-right 90° quadrant.
We can think of such a sensory system as an initial visual system. The pixel's value reflects the amount of blue in the corresponding visual field. If there is only one blue square, the pixel's value reflects the blue square's distance from Ernest. Green squares are opaque, meaning that blue squares behind green squares are not detected.
In the beginning of this example video, Ernest is trained the same way as in previous experiments. Then, the environment is opened and a blue square is added. We can see the two pixels on Ernest's head that reflect the detected blue. The closer the blue square, the more vivid the corresponding blue pixel.
Ernest 8.0 does not yet use this sensory system to inform his behavior. Making bottom-up intrinsic motivation and distal sense work together will be one of our next challenges.
We can think of such a sensory system as an initial visual system. The pixel's value reflects the amount of blue in the corresponding visual field. If there is only one blue square, the pixel's value reflects the blue square's distance from Ernest. Green squares are opaque, meaning that blue squares behind green squares are not detected.
In the beginning of this example video, Ernest is trained the same way as in previous experiments. Then, the environment is opened and a blue square is added. We can see the two pixels on Ernest's head that reflect the detected blue. The closer the blue square, the more vivid the corresponding blue pixel.
Ernest 8.0 does not yet use this sensory system to inform his behavior. Making bottom-up intrinsic motivation and distal sense work together will be one of our next challenges.
Monday, December 6, 2010
Java Ernest 7.2 in Vacuum
We put Ernest 7.2 back to the Vacuum environment to provide an example implementation of the Ernest Java class.
As we can see in this example video, the Java version is much faster than the Soar version. In fact, we had to slow the Java version down with timers to be able to see something.
This experiment uses the following settings:
- [move forward, succeed, 5] Ernest enjoys moving forward.
- [move forward, fail, -8] Ernest hates bumping walls.
- [turn left or right, succeed, 0] Ernest is indifferent of turning toward an empty square.
- [turn left or right, fail, -5] Ernest dislikes turning toward a wall.
- [touch, succeed, -1] Ernest slightly dislikes touching walls.
- [touch, fail, 0] Ernest is indifferent of touching empty squares.
As we can see in this example video, the Java version is much faster than the Soar version. In fact, we had to slow the Java version down with timers to be able to see something.
This experiment uses the following settings:
- [move forward, succeed, 5] Ernest enjoys moving forward.
- [move forward, fail, -8] Ernest hates bumping walls.
- [turn left or right, succeed, 0] Ernest is indifferent of turning toward an empty square.
- [turn left or right, fail, -5] Ernest dislikes turning toward a wall.
- [touch, succeed, -1] Ernest slightly dislikes touching walls.
- [touch, fail, 0] Ernest is indifferent of touching empty squares.
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