E.O. Wilson and B.F. Skinner have argued for an evolutionary ethics that allows what ought to be to be derived from what is-ethics from science. Evolution is inherently unpredictable, however, and some practices whose benefits cannot be proved might nevertheless turn out to be good for the survival of a culture or the race. Other practices that seem to be good might turn out to be bad. Consequently, the evolutionary argument implies that a successful culture will believe some things that cannot be proved, and it tells us that we cannot know in advance what those things will be.

Three experiments with pigeons studied the relation between time and rate measures of behavior under conditions of changing preference. Experiment 1 studied a concurrent chain schedule with random-interval initial links and fixed-interval terminal links; Experiment 2 studied a multiple chained random-interval fixed-interval schedule; and Experiment 3 studied simple concurrent random-interval random-interval schedules. In Experiment 1, and to a lesser extent in the other two experiments, session-average initial-link wait-time differences were linearly related to session-average response-rate differences. In Experiment 1, and to a lesser extent in Experiment 3, ratios of session-average initial-link wait times and response rates were related by a power function. The weaker relations between wait and response measures in Experiment 2 appear to be due to the absence of competition between responses. In Experiments 1 and 2, initial-link changes lagged behind terminal-link changes. These findings may have implications for the relations between fixed- and variable-interval procedures and suggest that more attention should be paid to temporal measures in studies of free-operant choice.

In the time-left experiment (J. Gibbon & R. M. Church, 1981), animals are said to compare an expectation of a fixed delay to food, for one choice, with a decreasing delay expectation for the other, mentally representing both upcoming time to food and the difference between current time and upcoming time (the cognitive hypothesis). The results of 2 experiments support a simpler view: that animals choose according to the immediacies of reinforcement for each response at a time signaled by available time markers (the temporal control hypothesis). It is not necessary to assume that animals can either represent or subtract representations of times to food to explain the results of the time-left experiment.

It is hard to know how to respond gracefully to a review as incomplete, inaccurate, and just plain ad-hominem grumpy as Baum's, but I will try.The review is ad hominem because Baum imputes motives-dishonorable ones-to me.It is inaccurate in numerous ways that I shall document.And it is incomplete because it fails to tell the reader what the book is about.First, Staddon's evil motives: ''As I read through his diatribe against Skinner . . .I wondered why Staddon would write this. . . .Most likely, it is a political move; he wants to distance himself from Skinner and to curry favor with the anti-Skinner psychologists and philosophers'' (p.76).A response is hardly necessar y, but I remind the reader that smearing the messenger if you can't deal with the message is a standard ''political move.''As for currying favor with the anti-Skinnerians, perhaps Baum missed the section in The New Behaviorism (TNB) headed Philosophical Objections to Cognitive Psychology, roughly half of chapter 6, which discussed several problems with the cognitive approach, including the homunculus fallacy, the competence-performance distinction (due to the anti-Skinnerian-in-chief, Noam Chomsky), lack of attention to motivation (Guthrie's objection to Tolman), and overinterpretation of straightforward experimental results, illustrated by Schachter and Wagner's (1999) imaginative comments on a brain-recording experiment published in Science.Or chapter 8, which refutes several cognitive accounts of phenomena related to consciousness.Or perhaps Baum failed to notice in this very journal the unenthusiastic reaction of cognitivists Gallistel and Gibbon to our critical treatment of scalar timing theory (Gallistel, 1999;Gibbon,

Interval timing in operant conditioning is the learned covariation of a temporal dependent measure such as wait time with a temporal independent variable such as fixed-interval duration. The dominant theories of interval timing all incorporate an explicit internal clock, or "pacemaker," despite its lack of independent evidence. The authors propose an alternative, pacemaker-free view that demonstrates that temporal discrimination can be explained by using only 2 assumptions: (a) variation and selection of responses through competition between reinforced behavior and all other, elicited, behaviors and (b) modulation of the strength of response competition by the memory for recent reinforcement. The model departs radically from existing timing models: It shows that temporal learning can emerge from a simple dynamic process that lacks a periodic time reference such as a pacemaker.

Memory decay is rapid at first and slower later—a feature that accounts for Jost's memory law: that old memories gain on newer ones with lapse of time. The rate-sensitive property of habituation—that recovery after spaced stimuli may be slower than after massed—provides a clue to the dynamics of memory decay. Rate-sensitive habituation can be modeled by a cascade of thresholded integrator units that have a counterpart in human brain areas identified by magnetic source imaging (MSI). The memory trace component of the multiple-time-scale model for habituation can provide a ‘clock’ that has the properties necessary to account for both static and dynamic properties of interval timing: static proportional and Weber-law timing as well as dynamic tracking of progressive, ‘impulse’ and periodic interval sequences.

Animals on interval schedules of reinforcement can rapidly adjust a temporal dependent variable, such as wait time, to changes in the prevailing interreinforcement interval. We describe data on the effects of impulse, step, sine‐cyclic, and variable‐interval schedules and show that they can be explained by a tuned‐trace timing model with a one‐back threshold‐setting rule. The model can also explain steady‐state timing properties such as proportional and Weber law timing and the effects of reinforcement magnitude. The model assumes that food reinforcers and other time markers have a decaying effect (trace) with properties that can be derived from the rate‐sensitive property of habituation (the multiple‐time‐scale model). In timing experiments, response threshold is determined by the trace value at the time of the most recent reinforcement. The model provides a partial account for the learning of multiple intervals, but does not account for scalloping and other postpause features of responding on interval schedules and has some problems with square‐wave schedules.

The “A-not-B” error is consistent with an old memory principle, Jost's Law. Quantitative properties of the effect can be explained by a dynamic model for habituation that is also consistent with Jost. Piaget was well aware of the resemblance between adult memory errors and the “A-not-B” effect and, contrary to their assertions, Thelen et al.'s analysis of the object concept is much the same as his, though couched in different language.

We report results from an experiment designed to study the perceptual and learning processes involved in the detection of land mines. Subjects attempted to identify the location of spatially distributed targets identified by a sweeping a cursor across a computer screen. Invisible screen "objects" were identified by either tones (A) or clicks (B) or both. Objects defined by a tone or a click only are distracters; the single object defined by both is the target (mine). We looked at the effect on target detectability of the number and spatial distribution of distracters. As expected from theoretical analysis, target detectability was highest when A and B distracters were negatively correlated; lowest when they were positively correlated. Under these conditions, detectability is was also inversely related to the number of A distracters (which were spatially diffuse) but was largely unaffected by the number of B distracters (which were punctate). Adding a second sensor channel greatly enhanced target detectability, especially if A and B distracters were spatially uncorrelated or negatively correlated.

We report preliminary results from an experiment designed to study the perceptual and learning processes involved in the detection of land mines. Subjects attempted to identify the location of spatially distributed targets identified by a sweeping a cursor across a computer screen. Each point on the screen was associated with a certain tone intensity; targets were louder than 'distractor' objects. We looked at the effects on target detection and false-alarm rates of the intensity difference between target and distractor signals, the number of distractor signals, the number of distractors and training order. The time to detect 50 percent of targets was measured by a rapid adaptive technique which generated reliable thresholds within few trials. The result are consistent with a simple model for the detection of cryptic prey by foraging predators: search was slower with more distractors, and the effect of distractors was greater when S/N ratio was lower. Although subjects got no accuracy feedback, performance improved somewhat with experience and was slightly better in the low S/N condition when it followed the high S/N condition. The procedure seems to be a useful one for studying more complex mine-related detection tasks with a range of signal types and numbers of concurrent detection signals.

In experiment 1, five goldfish (Carassius auratus) paddle-pressed on fixed-interval (FI) and variable-interval (VI) schedules for food pellet reinforcement. The order of conditions was FI 60 s, FI 240 s, FI 30 s, FI 60 s, and VI 60 s. FI responding showed a scalloped pattern and response-rate break points were proportional to interval duration. Post-food wait times varied with interval duration, but were not proportional. Response rate on VI was constant. Experiment 2 studied the properties of food reinforcement as a time marker. The same five fish were presented an FI 60 s schedule of reinforcement with 25% of intervals ending in non-reinforcement (N). The fish responded faster and paused less following the omission stimulus (omission effect) and response rate was flat or declined through post-N intervals.

Existing models of operant learning are relatively insensitive to historical properties of behavior and applicable to only limited data sets. This article proposes a minimal set of principles based on short-term and long-term memory mechanisms that can explain the major static and dynamic properties of operant behavior in both single-choice and multiresponse situations. The critical features of the theory are as follows: (a) The key property of conditioning is assessment of the degree of association between responses and reinforcement and between stimuli and reinforcement; (b) the contingent reinforcement is represented by learning expectancy, which is the combined prediction of response-reinforcement and stimulus-reinforcement associations; (c) the operant response is controlled by the interplay between facilitatory and suppressive variables that integrate differences between expected (long-term) and experienced (short-term) events; and (d) very-long-term effects are encoded by a consolidated memory that is sensitive to the entire reinforcement history. The model predicts the major qualitative features of operant phenomena and then suggests an experimental test of theoretical predictions about the joint effects of reinforcement probability and amount of training on operant choice. We hypothesize that the set of elementary principles that we propose may help resolve the long-standing debate about the fundamental variables controlling operant conditioning.

The tuned-trace multiple-time-scale (MTS) theory of timing can account both for the puzzling choose-short effect in time-discrimination experiments and for the complementary choose-long effect But it cannot easily explain why the choose-short effect seems to disappear when the intertrial and recall intervals are signaled by different stimuli. Do differential stimuli actually abolish the effect, or merely improve memory? If the latter, there are ways in which an expanded MTS theory might explain differential-context effects in terms of reduced interference. If the former, there are observational and experimental ways to determine whether differential context favors prospective encoding or some other nontemporal discrimination.

Objections to a trace hypothesis for interval timing do not apply to the multiple-time-scale (MTS) theory, which incorporates a dynamic trace tuned by the system history and can easily accommodate interval timing over a 1,000:1 range. The MTS model can also account for Weber's law as well as systematic deviations from it. Contrary to our critics, we contend that patterns of variance in interval timing experiments are not fully described by scalar expectancy theory, and that attempting to understand timing by assigning variance to different elements of a flexible model that lacks inductive support is a flawed strategy, because the attempt may be successful even if the model is wrong. We further argue that biological plausibility is an unreliable guide to the development of behavioral theory, that prediction is not the same as test, that induction should precede deduction, and that a rat is not a clock.

A popular view of interval timing in animals is that it is driven by a discrete pacemaker-accumulator mechanism that yields a linear scale for encoded time. But these mechanisms are fundamentally at odds with the Weber law property of interval timing, and experiments that support linear encoded time can be interpreted in other ways. We argue that the dominant pacemaker-accumulator theory, scalar expectancy theory (SET), fails to explain some basic properties of operant behavior on interval-timing procedures and can only accommodate a number of discrepancies by modifications and elaborations that raise questions about the entire theory. We propose an alternative that is based on principles of memory dynamics derived from the multiple-time-scale (MTS) model of habituation. The MTS timing model can account for data from a wide variety of time-related experiments: proportional and Weber law temporal discrimination, transient as well as persistent effects of reinforcement omission and reinforcement magnitude, bisection, the discrimination of relative as well as absolute duration, and the choose-short effect and its analogue in number-discrimination experiments. Resemblances between timing and counting are an automatic consequence of the model. We also argue that the transient and persistent effects of drugs on time estimates can be interpreted as well within MTS theory as in SET. Recent real-time physiological data conform in surprising detail to the assumptions of the MTS habituation model. Comparisons between the two views suggest a number of novel experiments.

Cognitive behaviorist E. C. Tolman (1932) proposed many years ago that rats and men navigate with the aid of cognitive maps, but his theory was incomplete. Critic E. R. Guthrie (1935) pointed out that Tolman's maps lack a rule for action, a route finder. We show that a dynamic model for stimulus generalization based on an elementary diffusion process can reproduce the qualitative properties of spatial orientation in animals: area-restricted search in the open field, finding shortcuts, barrier learning (the Umweg problem), spatial "insight" in mazes, and radial maze behavior. The model provides a behavioristic reader for Tolman's cognitive map. The cognitive behaviorist Edward Tolman spent much of his career devising clever experiments to show that stimulus-response accounts of rat behavior cannot be correct. Some of his most striking demonstrations involve spatial learning. One such example is shown in Figure 1, which depicts a maze apparatus used in a famous experiment by Tolman and Honzik (1930). The maze has three paths from the Start box to the Goal box. The paths differ in length: Path 1 (heavy vertical line) shorter than Path 2 (intermediate line) shorter than Path 3 (light line). In preliminary training, the rats were allowed to become familiar with all three paths to the Goal box. They also had experience with a block at Point A, which permits access to the Goal only via Paths 2 and 3. In the test condition, the block was moved to Point B--so that only Path 3 is open. The question is, Will the rats choose Path 3 as soon as they encounter the block at B, or will they choose Path 2, which is normally preferred to Path 3--indicating that they do not know Paths 1 and 2 share a common, blocked, segment? Tolman and Honzik's rats behaved intelligently and usually went straight to Path 3 after encountering the block at B. Tolman took this as evidence that the rats knew something about the topography of the maze. They were not just operating on a fixed hierarchy of preferences ( "Path 1 better than Path 2 better than Path 3" ), nor were they responding reflexively to local cues. Tolman considered this behavior to be an example of "insight," although he did not specify exactly what that means. He did say that some kind of cognitive map

Search strategy is an important component of any system that uses autonomous agents to detect and neutralize mines. We describe a simple and efficient search strategy derived from research on the adaptive spatial behavior of animals. Electromagnetic sensor data are processed to obtain a discrete spatial target distribution. The target distribution is used as input for a dynamic diffusion process. The diffusion surface is used by the demining agent to optimize its spatial moves through a hill climbing technique. The agent chooses to move to the position with the highest diffusion surface value. If the same diffusion surface is available to all agents, the system can be scaled to guide an indefinite number of independent, non-interfering agents.

Memory dynamics, the effects on recall of the temporal spacing of to-be-remembered stimuli, reflect three processes: learning, forgetting (trace decay), and interference. A process for trace decay can be derived from a cascaded-integrator model for rate-sensitive habituation. The model predicts nonexponential forgetting functions that are compatible with Jost's law (old memories decay more slowly than new) as well as the 2-parameter summary functions recently derived from a massive dataset on human retention. The same process seems to be involved in other reaming phenomena such as the partial reinforcement extinction effect and reinforcement successive-contrast effects.

A local diffusion model (Staddon and Reid, 1990) can reproduce exponential and Gaussian stimulus-generalization gradients. We show that a two-dimensional diffusion model, together with simple reinforcement assumptions, can reproduce many of the empirical properties of goal-directed spatial search, including area-restricted search, open-field foraging, barrier and detour problems, maze learning and spatial “insight.” The model provides a simple, associationistic “reader” for Tolman's cognitive map.