Let’s give Tadro3 simple wheels. The simplest wheels spin but don’t turn. Tadro3 turns by having different levels of power go to the two motors that drive the wheels. Having two motors to turn in the wheeled Tadro3 is the functional equivalent of having two muscles, working in pairs, to control the direction of the tail for turning in the swimming Tadro3 (Figure 5.3). Also notice that the simplest neural circuit is used here: a single light sensor provides both an excitatory and inhibitory signal. The cup-shaped light sensor is directional in the sense that it registers light only when that light hits its concave surface directly (not by coming through the back of the cup).
FIGURE 5.5. Vehicular Tadro3 (vT3) turns in response to light. In this thought experiment, when no light is hitting the cup-shaped light receptor, vT3 arcs to the right. When the receptor faces the light and is close enough to register the light, its path straightens as more power is delivered to the right wheel’s motor and less is delivered to the left wheel’s motor. The vT3 is inspired by the vehicles of Valentino Braitenberg.
How does vehicular Tadro3, or “vT3” for short, behave? It’s time for a thought experiment, a cognitive simulation (Figure 5.5). First, suppose that vT3 has an intrinsic rate of wheel spinning and is always moving around. When vT3 is in the dark, the left motor gets a bit more power than the right, so vT3 arcs to the right. As soon as light falls on vT3’s light sensor, though, the right motor starts to get more power, and the left gets some of its power reduced because of inhibition. When this happens, vT3 straightens out its heading.
Doing thought experiments like this, with a wheeled vehicle and a simple sensory-motor circuit, was the brainchild of Valentino Braitenberg, a neuroanatomist. His 1984 book, Vehicles: Experiments in Synthetic Psychology, inspired a generation of workers in artificial intelligence and behavior-based robotics. By taking the reader through thought experiments with an evolving fleet of Vehicles, Braitenberg creates the “law of uphill analysis and downhill invention.” This law is drawn from what we would be tempted to call a functionalist observation: “It is actually impossible in theory to determine exactly what the hidden mechanism is without opening the box, since there are always many different mechanisms with identical behavior.”[94]
Braitenberg calls analysis “uphill” because “when we analyze a mechanism, we tend to overestimate its complexity.”[95] From Braitenberg we can see that anyone interested in understanding the mechanistic basis of behavior, including the behavior that we call intelligence, either has to open the box, as we did with our Searle hat on, or, as Braitenberg did, take the “downhill invention” route and create behavior from the ground up, like an engineer applying the secret code.
When we morphed Tadro3 into vT3, we showed that at least two mechanisms, two neural circuits in our case, could drive the sensory-motor responses to light. We also used Braitenberg’s approach to show how little—in terms of circuitry—that Tadro3 needs in order to behave. Nowhere in the circuits of Tadro3 or vT3 do we see a collection and connection of interneurons that we’d be tempted to call a brain.
Braitenberg Vehicles are brainless and yet still manage to exhibit what, to the observer of the Vehicle who is blind to the Vehicle’s internal mechanism, we would call intelligence, at least at the level of goal-directed, purposeful autonomy. To be fair, though, we haven’t shown that vT3 actually works; we only ran the simulation in our minds. For part of his senior thesis in cognitive science at Vassar, Adam Lammert implemented the vT3 circuit on a wheeled robot to see if it worked as we had imagined. It did (Figure 5.6).
Because embodied Braitenberg Vehicles work both in physical reality and in simulation, we can use them to explore what kinds of bodies make behavior and what kinds don’t (Figure 5.7).
In this embodied view you can see right away what’s needed to be an autonomous agent. With a single sensor and a single wheel, what Braitenberg called a Vehicle of brand 1, this simplest autonomous Vehicle will speed up if it is facing a light source and slow down if not.
FIGURE 5.6. The vT3 operating as an embodied and autonomous wheeled robot. Top panel shows the arc-like path of vT3 over the course of a three-minute experiment run by Adam Lammert. When the path turns from gray to black, vT3 has detected the light. The bottom panel shows what happens when vT3 detects the light. At about ten seconds into the trial vT3 detects the light and changes its heading by almost 55 degrees, straightening out its arc, heading toward the light, and then orbiting it. Keep in mind that vT3 can be thought of as a Braitenberg Vehicle of brand 1.5.
FIGURE 5.7. The embodied view: intelligence is what we do autonomously. In a thought experiment created by Valentino Braitenberg, simple vehicles can have sensors attached directly to actuators, without an intervening brain. Without a sensor, an actuator, and a connection between them, the vehicle cannot behave because it has no way to sense or move. To have autonomous behavior, a sensor must be connected to an actuator. Here is a simple thought experiment: take the autonomous vehicle with one light sensor, one motorized wheel, and an excitatory connection between them. Put a light in front of this vehicle. What happens?
Although this isn’t terribly exciting behavior, it is behavior as we’ve defined it: the interaction of the agent and the environment. Vehicle 1 shows that what’s necessary and sufficient for behavior is (1) a sensor connected to a motor, (2) the sensory-motor linkage embodied in a chassis that has an actuator, (3) the Vehicle situated in an environment with a variable energy field that the sensor can detect, and (4) the Vehicle situated in an environment with a substrate to which the actuator can transfer its momentum. Behavior is impossible if any of these features are missing.
If you study these Braitenberg Vehicles (Figure 5.7), you can see where vT3 might belong: between the first and second autonomous Vehicles. In the lexicon of Braitenberg vT3 is thus neither a Vehicle of brand 1 (single sensor, single motor) nor a Vehicle of brands 2 or 3 (double sensor, double motor). In recognition of its intermediate character, Lammert called vT3 Vehicle 1.5. We can characterize Vehicle 1.5 not only graphically (Figure 5.4) but also by using the parameter space for Vehicles (Figure 5.7): (1) one sensor, (2) two actuators, (3) two connections from the one sensor, (4) one connection to each motor, and (5) both excitatory and inhibitory connections.
No brain? No problem. As Tadro3, vT3, and Braitenberg Vehicle of brand 1.5 all show, we can build autonomous agents without what Professor Rodney Brooks of the Massachusetts Institute of Technology calls the “cognition box.” Brooks, a mainstream member of the world of artificial intelligence, revolutionized AI in the 1980s. While others had slow-moving robots burdened with computationally intensive problems like vision, path planning, and world mapping, Brooks built simple robots that could literally run circles around their more complex brethren.[96]
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Valentino Braitenberg,
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Brooks chronicles this revolution: Rodney A. Brooks,